{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"431ba833-ac4a-4ffc-b1eb-ea585214fc8c","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Mission Operations Product Manager, Group 5 Mission Autonomy","slug":"mission-operations-product-manager-group-5-mission-autonomy-96b19d8b","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n WHAT YOU’LL DO   \n \n Develop Mission Autonomy products that support the operation of Group 5 autonomous air vehicles \n Drive product development for the entire lifecycle from initial requirements development to fielding\n Define product roadmaps and timelines, guide cross-functional product decisions, and manage engineering risk\n Working closely with engineering leads and business development, evaluate trades to enable exploration of early designs\n Develop autonomy behavior and supporting product requirements. Collaborate with engineering teams to implement requirements\n Work collaboratively with cross-functional teams, including software engineers, hardware engineers, test engineers, and program managers, to define test requirements and ensure alignment between system capabilities and mission objectives in complex operational scenarios\n Plan, execute, and analyze mission autonomy tests in simulated environments that replicate real-world scenarios to validate system performance and identify areas for improvement, iterating rapidly to refine autonomy behaviors and supporting products\n Support business development teams by being the product voice at the table with customers through customer briefings/demonstrations/exercises\n Support business development in creating and maintain updated presentation templates of product capabilities that can be used as an 80% solution for customer briefs\n \n   \n REQUIRED QUALIFICATIONS   \n \n Operational experience as a Pilot or CSO/NFO of USAF, USN, USMC 4th or 5 th generation fighter/bomber aircraft or RPAs \n Self-starter with high ownership, mission-oriented mentality. Desire to see the product meet the need of the end customer\n Strong analytical skills, with the ability to interpret test data, diagnose system behaviors, and recommend actionable improvements\n Organized and detail-oriented, with strong verbal \u0026 written communication skills\n Proven track record of working collaboratively with multidisciplinary teams to achieve project milestones and deliverables\n Experience in leading system design and development from initial concept through delivery to customers\n Ability to leverage operational experience and technical knowledge to make educated decisions and leverage engineering trades in the absence of clear customer requirements\n Willingness to work flexible hours. Up to 25% travel as required for customer engagements and product development activities\n Active U.S. Top Secret security clearance and experience with Special Access Programs   \n \n PREFERRED QUALIFICATIONS   \n \n 5th generation aircraft pilot experience preferred \n Weapons school instructor, weapons school graduate, test pilot school graduate, Developmental or Operational Test experience\n Bachelor’s degree in STEM, or equivalent experience in a relevant field\n Direct experience in the development, testing, and deployment of mission autonomy systems in a defense or aerospace context\n Familiarity with agile software development practices \n Knowledge of current industry and military standards related to unmanned aerial systems and their operation within national airspace\n Familiarity with the principles of mission autonomy, unmanned systems, and the integration of multiple assets into cohesive operational frameworks\n US Salary Range\n $191,000 — $253,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidat","salary_min":191000,"salary_max":253000,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["computer-vision","cloud","payments","fine-tuning"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5265377007?gh_jid=5265377007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-14T13:10:03Z","expires_at":"2026-11-13T16:57:15.893852Z","created_at":"2026-10-14T15:21:01.028112Z","updated_at":"2026-10-14T16:57:15.896738Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/431ba833-ac4a-4ffc-b1eb-ea585214fc8c"},{"id":"8e20950b-3b3e-46d3-bbbc-c7144188aaa9","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Mission Operations Product Manager, Group 5 Mission Autonomy","slug":"mission-operations-product-manager-group-5-mission-autonomy-36628482","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n WHAT YOU’LL DO   \n \n Develop Mission Autonomy products that support the operation of Group 5 autonomous air vehicles \n Drive product development for the entire lifecycle from initial requirements development to fielding\n Define product roadmaps and timelines, guide cross-functional product decisions, and manage engineering risk\n Working closely with engineering leads and business development, evaluate trades to enable exploration of early designs\n Develop autonomy behavior and supporting product requirements. Collaborate with engineering teams to implement requirements\n Work collaboratively with cross-functional teams, including software engineers, hardware engineers, test engineers, and program managers, to define test requirements and ensure alignment between system capabilities and mission objectives in complex operational scenarios\n Plan, execute, and analyze mission autonomy tests in simulated environments that replicate real-world scenarios to validate system performance and identify areas for improvement, iterating rapidly to refine autonomy behaviors and supporting products\n Support business development teams by being the product voice at the table with customers through customer briefings/demonstrations/exercises\n Support business development in creating and maintain updated presentation templates of product capabilities that can be used as an 80% solution for customer briefs\n \n   \n REQUIRED QUALIFICATIONS   \n \n Operational experience as a Pilot or CSO/NFO of USAF, USN, USMC 4th or 5 th generation fighter/bomber aircraft or RPAs \n Self-starter with high ownership, mission-oriented mentality. Desire to see the product meet the need of the end customer\n Strong analytical skills, with the ability to interpret test data, diagnose system behaviors, and recommend actionable improvements\n Organized and detail-oriented, with strong verbal \u0026 written communication skills\n Proven track record of working collaboratively with multidisciplinary teams to achieve project milestones and deliverables\n Experience in leading system design and development from initial concept through delivery to customers\n Ability to leverage operational experience and technical knowledge to make educated decisions and leverage engineering trades in the absence of clear customer requirements\n Willingness to work flexible hours. Up to 25% travel as required for customer engagements and product development activities\n Active U.S. Top Secret security clearance and experience with Special Access Programs   \n \n PREFERRED QUALIFICATIONS   \n \n 5th generation aircraft pilot experience preferred \n Weapons school instructor, weapons school graduate, test pilot school graduate, Developmental or Operational Test experience\n Bachelor’s degree in STEM, or equivalent experience in a relevant field\n Direct experience in the development, testing, and deployment of mission autonomy systems in a defense or aerospace context\n Familiarity with agile software development practices \n Knowledge of current industry and military standards related to unmanned aerial systems and their operation within national airspace\n Familiarity with the principles of mission autonomy, unmanned systems, and the integration of multiple assets into cohesive operational frameworks\n US Salary Range\n $191,000 — $253,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidat","salary_min":191000,"salary_max":253000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["payments","computer-vision","fine-tuning","cloud"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5247776007?gh_jid=5247776007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-14T13:10:01Z","expires_at":"2026-11-13T16:57:15.88163Z","created_at":"2026-10-14T15:21:01.032558Z","updated_at":"2026-10-14T16:57:15.885257Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8e20950b-3b3e-46d3-bbbc-c7144188aaa9"},{"id":"19f2bcb8-dfcf-45a4-b0a7-855bfd707cfa","company_id":"2114efab-ea67-411b-bfb8-7899153105f3","title":"Engineering Manager","slug":"engineering-manager-3cdfd46c","description":"Overview\n\nInferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.\n\nAbout the Role\n\nWe're looking for an Engineering Manager to help scale a world-class, senior-heavy engineering organization working at the frontier of AI inference. You will lead a team of exceptional engineers across areas such as inference systems, performance, kernels, accelerators, and cloud infrastructure while creating the management capacity required for Inferact to keep growing quickly without sacrificing technical quality or execution speed.\n\nThis is a deeply technical management role. You will own team execution, hiring, coaching, prioritization, and operating rhythm, while staying close enough to the work to earn the trust of engineers solving hard systems problems. You will partner closely with engineering and company leadership to turn company priorities into clear technical direction, remove blockers, improve how the team works, and help every engineer do the highest-leverage work of their career.\n\n\n\nSkills and Qualifications\n\nMinimum qualifications:\n\n - Bachelor's degree or equivalent experience in computer science, engineering, or similar.\n\n - Demonstrated experience managing strong software engineers in technically demanding systems, infrastructure, ML systems, distributed systems, or performance-oriented environments.\n\n - Strong technical credibility with the ability to understand architecture, ask useful questions, challenge assumptions, and help unblock senior engineers without becoming a bottleneck or overriding domain experts.\n\n - Experience owning the full people-management lifecycle, including hiring, onboarding, 1:1s, feedback, performance management, career development, team health, and retention.\n\n - Ability to translate ambiguous company priorities into clear team goals, sequencing, ownership, and execution plans while maintaining urgency in a fast-changing startup environment.\n\n - Track record of building effective engineering operating rhythms around planning, decision-making, technical reviews, cross-team coordination, and accountability without creating unnecessary process.\n\n - Strong judgment about when to dive into a technical problem, when to delegate, and how to create leverage for senior engineers rather than competing with them for ownership.\n\n - 2+ years of management experience with 10+ reports.\n\nPreferred qualifications:\n\n - Experience leading teams working on AI / ML infrastructure, model serving, distributed systems, GPU infrastructure, compilers, performance engineering, cloud infrastructure, or developer platforms.\n\n - Experience managing senior, staff, principal, research-adjacent, or PhD engineers in an environment where technical credibility and autonomy are especially important.\n\n - Experience scaling an engineering team through rapid hiring, including interviewer calibration, hiring decisions, onboarding systems, and thoughtful team design.\n\n - Familiarity with inference systems and adjacent technologies such as vLLM, SGLang, PyTorch, CUDA / Triton, Kubernetes, distributed serving, or accelerator infrastructure.\n\n - Experience partnering closely with founders or engineering executives in an early-stage company where priorities, team boundaries, and organizational needs evolve quickly.\n\nBonus points if you have:\n\n - Built or scaled a small, unusually high-talent engineering team where the technical surface area was specialized and the quality bar was extremely high.\n\n - Previously remained hands-on as an engineer or technical lead before moving into management and can still reason credibly about complex production systems.\n\n - Managed teams spanning multiple technical specialties, geographies, or time zones while preserving strong ownership and communication.\n\n - Helped establish engineering management practices from an early stage rather than inheriting a mature management system.\n\n - Contributed to open-source infrastructure, AI systems, developer tools, or technically ambitious products used by external engineers.\n\nLogistics\n\n - Location: This role is based in San Francisco, California and is in-office.\n\n - Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.\n\n - Visa sponsorship: We sponsor visas on a case-by-case basis.\n\n - Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["cloud","llm","pytorch","gpu","mlops","distributed-systems","research"],"apply_url":"https://jobs.ashbyhq.com/inferact/98837c38-33a9-4085-97e7-1974dcf234a1/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-14T11:23:31.216Z","expires_at":"2026-11-13T16:58:50.529662Z","created_at":"2026-10-14T15:22:31.292734Z","updated_at":"2026-10-14T16:58:50.533097Z","company_name":"Inferact","company_slug":"inferact","company_logo_url":"https://www.google.com/s2/favicons?domain=inferact.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/19f2bcb8-dfcf-45a4-b0a7-855bfd707cfa"},{"id":"8ad2920a-4171-4759-864b-2007360008f4","company_id":"3dacb2af-b4b4-42ae-9b16-4e0203d290e4","title":"Machine Learning Engineering Intern, Summer 2027","slug":"machine-learning-engineering-intern-summer-2027-53172cc3","description":"About Wing:  \n Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us. \n About the Program:  \n Join Wing's 12-week paid summer internship! This is a hybrid, in-person program based in Palo Alto, CA, with start dates in May or June. Eligible candidates must be a current student enrolled in a degree program and intend to return to the program after the completion of the summer internship. \n About the Opportunity: \n Wing is looking for a Machine Learning Engineer Intern to join our Perception team based in Palo Alto, CA. You will be at the forefront of advancing our autonomous drone delivery system, leveraging deep learning to ensure our aircraft navigate the world with precision and safety.  At Wing, you aren’t just building models in a vacuum; you have access to tens of thousands of hours of flight data from a diverse sensor suite\n In this role, you will: \n \n Help us track towards our goal of building unified and/or generalized Perception models that helps Wing aircraft systems gracefully handle a wide variety of edge cases they experience when operating in the real world\n Analyze real-world data, coming up with new ideas on how to improve our existing Perception pipelines with state-of-the-art foundational and end-to-end geometric models\n Gain experience with leveraging large amounts of diverse, real-world data from a fleet of thousands of robots to build ML models that solve real problems.\n Make a measurable impact on Wing's ability to scale our operations more rapidly, at the forefront of the rapidly growing drone delivery industry.\n Be a part of a dynamic and collaborative team.\n \n What You’ll Need:  \n \n Currently pursuing a Master's, or PhD degree in Aerospace Engineering, Mechanical Engineering, Computer Science, Computer Vision, Robotics, Electrical Engineering, or related field, graduating between December 2027 and August 2028\n Strong examples of previous engineering experience from past internships and/or academic or extracurricular projects.\n Strong grasp of basic physics and engineering fundamentals in Computer vision\n Strong grasp of modern computer vision technologies such as self-supervised Vision Transformer foundation model, Vision Language Models, VLAs, and hands-on experience in at-least one of those domains\n Experience with C++ and/or Python.\n The US base salary range for this internship position is the salary range below + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process.\n Salary Range\n $128,000 — $135,000 USD \n Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.\n If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our  Candidate Accommodations Request Form .","salary_min":128000,"salary_max":135000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["robotics","computer-vision","cloud","deep-learning","generative-ai","machine-learning"],"apply_url":"https://wing.com/careers/8872479002?gh_jid=8872479002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T22:00:01Z","expires_at":"2026-11-13T17:02:54.727732Z","created_at":"2026-10-14T15:24:57.757978Z","updated_at":"2026-10-14T17:02:54.730712Z","company_name":"Wing","company_slug":"wing","company_logo_url":"https://www.google.com/s2/favicons?domain=wing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8ad2920a-4171-4759-864b-2007360008f4"},{"id":"1a82c95f-d83c-420a-b3ab-74958d3adc4b","company_id":"3dacb2af-b4b4-42ae-9b16-4e0203d290e4","title":"Simulation Engineering Intern, Summer 2027","slug":"simulation-engineering-intern-summer-2027-747b710c","description":"About Wing:  \n Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us. \n About the Program:  \n Join Wing's 12-week paid summer internship! This is a hybrid, in-person program based in Palo Alto, CA, with start dates in May or June. Eligible candidates must be a current student enrolled in a degree program and intend to return to the program after the completion of the summer internship. \n About the Role: \n Wing is looking for a Simulation Engineer Intern to join our Simulation \u0026 Evaluation Team based in Palo Alto, CA . \n Our team develops tools that enable engineers to develop, test and deploy features efficiently and at scale. Our work spans vehicle physics and sensor modeling, large-scale simulation frameworks, test infrastructure for backend verification, integrated avionics and system testing, and foundational ML technologies such as world-modelling, 3D reconstruction and sim2real. Our team is dedicated to ensuring simulation is the fastest and most reliable way to test changes to our system and to enable safer and faster feature development.\n The successful candidate is able to demonstrate adeptness at software development, system modeling and simulation, 3D geometry, and RL techniques. We are looking for individuals with strong written and verbal communication skills who thrive collaborating across multidisciplinary teams, spanning Simulation, Perception, and GNC, and who can tackle complex, open-ended engineering problems.\n In this role you will:  \n \n Explore new and creative ways to use our wealth of real-world flight data to help validate our flight software.\n Build closed-loop simulation environments using real flight telemetry to enable counterfactual rollouts and policy evaluation for RL-based flight autonomy\n Leverage large-scale simulation and data pipelines to run critical experiments, draw actionable engineering insights, and contribute alongside a dedicated team committed to supporting your mentorship and growth.\n Make a measurable impact on Wing's ability to scale our operations more rapidly, at the forefront of the rapidly growing drone delivery industry.\n \n What You’ll Need:  \n \n Currently pursuing a Bachelor's, Master's or PhD degree in Aerospace Engineering, Mechanical Engineering, Computer Science, Computer Vision, Robotics, Electrical Engineering or related field, graduating between December 2027 and August 2028.\n Strong examples of previous engineering experience from past internships and/or academic or extracurricular projects.\n Strong grasp of dynamical systems, linear algebra, 3D geometry, and vision-based autonomy.\n Experience with C++ and/or Python.\n Experience with using some numerical or statistics library and environment (e.g. numpy, scipy, pandas, Matlab, R, etc.) to analyze real-world data (e.g. fitting models, simple ML approaches).\n Strong written and verbal communication skills with the ability to explain complex technical concepts across disciplines.\n The US base salary range for this internship position is the salary range below + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process.\n Salary Range\n $128,000 — $135,000 USD \n Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.\n If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our  Candidate Accommodations Request Form .","salary_min":128000,"salary_max":135000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["robotics","computer-vision","computer-graphics","data-pipeline","cloud"],"apply_url":"https://wing.com/careers/8872478002?gh_jid=8872478002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T22:00:01Z","expires_at":"2026-11-13T17:02:54.772498Z","created_at":"2026-10-14T15:24:57.804897Z","updated_at":"2026-10-14T17:02:54.775169Z","company_name":"Wing","company_slug":"wing","company_logo_url":"https://www.google.com/s2/favicons?domain=wing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1a82c95f-d83c-420a-b3ab-74958d3adc4b"},{"id":"972adbf0-5b20-4db8-9e6c-f42932f2c665","company_id":"76c63eb7-c307-4322-8c2b-c20216feec49","title":"Principal Software Engineer, Agentic Data Platform","slug":"principal-software-engineer-agentic-data-platform-70ab45e1","description":"Get to Know Us\n\nHorizon3.ai http://Horizon3.ai is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find, fix and verify exploitable attack vectors before criminals exploit them. Our flagship product, the NodeZero™ platform, delivers production-safe autonomous pentests and other key assessment operations that scale across the largest internal, external, cloud, and hybrid cloud environments. NodeZero has been adopted by organizations of all sizes, from small educational institutions to government agencies and Global 100 enterprises. It is used by IT Ops/SecOps teams, consulting pentesters, and MSSPs and MSPs.\n\nWe are a fusion of former U.S. Special Operations cyber operators, startup engineers \u0026 operators, and formerly frustrated cybersecurity practitioners. We're committed to helping solve our common security problems: ineffective security tools and false positives, resulting in alert fatigue, blind spots, \"checkbox\" security culture, cybersecurity skills shortage, and the long lead time and expense of hiring outside consultants. Collectively, we are a team of learn-it-alls, committed to a culture of respect, collaboration, ownership, and results.\n\nAs a remote first company, we require minimum 25Mbps consumer grade broadband connection.\n\n \n\nWhat You'll Do\n\nThe Principal Engineer for Database Platform is the technical anchor of NodeZero's data infrastructure. This is an individual contributor role with no direct reports — your influence is through technical leadership, architecture ownership, and raising the engineering bar across the team. You own the most consequential database architecture decisions, define the standards that govern how NodeZero stores, queries, and migrates data at scale, and ensure the data layer can support NodeZero's growth — more customers, larger environments, more pentest data — without requiring proportional operational effort. This is a deeply hands-on role: you will write code, author design documents, and set the technical direction that every engineer on the Database Platform team builds toward.\n\nNodeZero's data layer is not simple. We store millions of discovered assets, graph-structured attack paths, time-series vulnerability data, and audit-critical pentest results — across a multi-tenant architecture where correctness and data isolation are non-negotiable. You will be the person who makes the hardest data architecture calls and ensures the team has the technical foundations to build reliably on.\n\n - Technical Strategy: Define and drive the technical roadmap for the Database Platform in partnership with the Senior Engineering Manager and the broader Pentest Platform organization.\n\n - Architecture Leadership: Own the most complex database architecture decisions — schema design, partitioning strategies, migration patterns, and scalability approaches. Produce design documents that become the shared technical model for the team.\n\n - PostgreSQL Excellence: Be NodeZero's definitive expert on PostgreSQL at scale — query optimization, indexing, partitioning, replication, and connection pooling. Set the standards the team follows and catch the problems others miss.\n\n - Graph \u0026 Multi-model Data: Architect and guide the evolution of NodeZero's graph-based asset model — the data structure that represents how discovered hosts, services, credentials, and vulnerabilities relate to each other across pentests.\n\n - Schema Governance: Own schema design review processes. Ensure every migration is safe, reversible, and zero-downtime. Build the tooling and culture that treats schema changes with the same rigor as production code changes.\n\n - Mentorship \u0026 Bar Raising: Mentor P5 and P4 engineers through code review, design review, and pairing. Be the person on the team that raises everyone else's ceiling.\n\n - Cross-functional Influence: Partner with Data Ingestion, Asset Inventory, API Platform, and Security Research to define data contracts, query performance standards, and architectural guardrails that span the full data pipeline.\n\n \n\nWhat You'll Bring\n\nTechnical Depth\n\n - Deep, production-proven PostgreSQL expertise: query planner internals, advanced indexing (partial, expression, GiST/GIN), partitioning strategies, logical replication, vacuuming at scale, and connection pool tuning.\n\n - Experience architecting multi-tenant databases at scale: row-level security, tenant isolation, schema-per-tenant vs. shared-schema tradeoffs.\n\n - Experience with schema migration at scale in production systems: zero-downtime migrations, backwards-compatible schema evolution, and migration tooling (Flyway, golang-migrate, or equivalent).\n\n - Familiarity with graph data models and graph databases (Neo4j, AWS Neptune) or graph-like query patterns in relational systems (recursive CTEs, ltree, adjacency list).\n\n - Proficient in Go or Python — able to write production application code, not just SQL.\n\nArchitecture \u0026 Design\n\n - Demonstrate","salary_min":255000,"salary_max":290000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["security","agents","cloud","data-pipeline","platform"],"apply_url":"https://jobs.ashbyhq.com/horizon3ai/61bab297-9f6c-40d8-a7af-99ff61066943/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T20:23:08.726Z","expires_at":"2026-11-13T16:56:49.961684Z","created_at":"2026-10-14T15:20:34.974801Z","updated_at":"2026-10-14T16:56:49.964715Z","company_name":"Horizon3 AI","company_slug":"horizon3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=horizon3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/972adbf0-5b20-4db8-9e6c-f42932f2c665"},{"id":"bfd991d3-7f62-425c-bcfb-f01c579b3fb5","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Software Engineer, Data and AI Platform","slug":"software-engineer-data-and-ai-platform-a47789b0","description":"DoorDash is building the world's most reliable on-demand, logistics engine for delivery! We're looking for talented engineers to help us develop a 24x7, global infrastructure system that powers DoorDash's three-sided marketplace of consumers, merchants, and dashers.\n About the Team \n Data Platform’s Data User Experience Engineering builds the products every DoorDash employee uses to answer questions with data. That portfolio includes our AI first reporting and authoring surface,Conversational analytics with AI, Semantic and Knowledge layer along with MCP and skills layer plus the full stack infrastructure that lets users and agents reach all of it. Our users span analysts, engineers, operators, and executives across DoorDash, Wolt, and Deliveroo, on a warehouse and OLAP footprint that includes Snowflake,Spark and Clickhouse. The team is a mix of engineers who have built AI \u0026 Data platforms and products at scale.\n About the Role \n You will own the full path from a question to an answer an operator can put in a deck without checking it twice. The BI reporting surfaces are converging, and deciding what that convergence looks like while someone is authoring, building a report, writing a query, asking why a number moved, or asking for the chart they were about to build by hand.\n You’re excited about this opportunity because you will… \n \n Ship agentic analytics features to thousands of users  where a wrong number is a real business decision made badly, and accuracy is the product\n Build a data platform for authoring, dashboard runtime, drill-down and cross-filter semantics, scheduling and alerting, content certification and permissions, and the embedding path that puts the same components in front of external users\n Streaming large result sets to the browser, rendering dozens of interdependent tiles.\n Build the AI experience inside that platform: agent-assisted query authoring, generated charts and widgets held to the same governance as hand-built ones\n Evolve the semantic layer  metric and dimension modeling, definition governance, lineage  and expose metadata in forms a model can actually reason over\n Own the query and adaptive caching path: planning and federation across different query engines and invalidation correctness, and safe execution under agent traffic that bursts and fans out\n Develop AI-enabled services and workflows, including self-serve tooling for creating, evaluating, and improving AI assistants\n Build and operate data discovery and metadata platforms that help users find the right datasets, dashboards, and metrics quickly and confidently\n \n We're excited about you because you have… \n \n B.S., M.S., or PhD. in Computer Science or equivalent\n 3+ years of industry experience in software engineering\n Strong backend fundamentals, especially in Go,Python and the ability to own a service in production \n Shipped an LLM-powered feature to real users, hands-on with retrieval and grounding and built or meaningfully extended an eval system\n Built meaningful pieces of data platform products- semantic layers, data discovery, reporting applications, caching systems and data applications\n Familiarity with a cloud-based environment such as AWS and with Kubernetes in production\n Experience with MCP, agent frameworks, or tool-calling architectures in production\n Experience with traditional and modern reporting or analytics tooling, data governance, controls and multi-tenant data platforms\n Prompt and context optimization at scale -  caching, token budgeting, cost/latency tuning\n Full stack experience is a plus\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if","salary_min":130600,"salary_max":192000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["fine-tuning","llm","cloud","healthcare","computer-graphics","agents"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8192187","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T20:21:21Z","expires_at":"2026-11-13T17:03:28.751716Z","created_at":"2026-10-14T15:25:31.393614Z","updated_at":"2026-10-14T17:03:28.754637Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bfd991d3-7f62-425c-bcfb-f01c579b3fb5"},{"id":"b34f4013-d975-493b-8a19-92a0a531c511","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Software Engineer, Machine Learning","slug":"staff-software-engineer-machine-learning-c84454fb","description":"About the Team \n DoorDash is building the world's most reliable on-demand, logistics engine for delivery. We are continuing to grow rapidly and expanding our Engineering offices globally! We are looking for Software Engineers, Machine Learning to build and maintain a large scale 24x7 global infrastructure system that powers DoorDash's 3-sided marketplace of Consumers, Merchants and Dashers.\n About the Role \n As a Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph at the heart of our fast-growing grocery and retail delivery business.  You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams.\n This role is hybrid with some in-office time expected and will report to an Engineering Manager. \n You're excited about this opportunity because you will... \n \n Develop advanced machine learning models to improve ads efficiency and quality.\n Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals. \n Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue. \n Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience.\n Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.\n Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentation.\n Scale our systems and services to fuel the growth of our business.\n \n We're excited about you because you have... \n \n M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent.\n 8+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.\n Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software\n Experience building data/feature engineering pipelines at scale using Pyspark and Snowflake SQL.\n Experience with building machine learning systems in production by using frameworks such as PyTorch, Keras, LightGBM, scikit-learn, Spark ML, or related.\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).\n \n The national base pay range for this position within the United States, including Illinois and Colorado.\n $203,500 — $299,300 USD \n About DoorDash\n At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","cloud","healthcare","fine-tuning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8092262","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:49:36Z","expires_at":"2026-11-13T17:03:28.820143Z","created_at":"2026-10-14T15:25:31.461436Z","updated_at":"2026-10-14T17:03:28.823202Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b34f4013-d975-493b-8a19-92a0a531c511"},{"id":"2bdabd0b-9451-4388-b502-2ba7d839c43f","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Machine Learning Engineer, Drive","slug":"senior-machine-learning-engineer-drive-202e134e","description":"About the Team\n DoorDash Drive powers deliveries placed through merchants' own channels—including their websites, mobile apps, and phone orders—using DoorDash's logistics network. The Drive Machine Learning team builds the prediction and intelligence systems that power this business, including delivery and pickup time estimation, merchant prep-time prediction, order release optimization, logistics decision-making, and AI-powered delivery quality signals. Drive presents a unique machine learning challenge. Every merchant has different operational workflows, preparation patterns, and customer expectations, requiring models that generalize across millions of deliveries while adapting to highly diverse merchant behavior. Our team has significant opportunities to improve prediction accuracy, optimize logistics decisions, and build AI-native experiences that directly improve merchant, consumer, and dasher outcomes.\n About the Role\n As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration. Your work will span several high-impact problem areas:\n \n Build next-generation machine learning models for delivery ETA, pickup ETA, merchant prep-time estimation, and order release prediction that improve reliability for merchants and consumers.\n Develop deep learning models that leverage large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.\n Apply reinforcement learning and optimization techniques to improve logistics decision-making, assignment strategies, and marketplace efficiency.\n Build AI-native product experiences using large language models (LLMs) and vision-language models (VLMs). For example, transform pickup photos, item verification flows, receipts, and drop-off images into structured quality signals that help verify orders, prevent delivery defects, and improve issue resolution.\n Design and run rigorous online experiments, production monitoring, and model iteration to continuously improve performance.\n Partner closely with software engineers, product managers, data scientists, and platform teams to bring new machine learning capabilities into production at scale.\n You'll have the opportunity to work across traditional machine learning, deep learning, reinforcement learning, optimization, and multimodal AI while solving some of the most challenging logistics problems at DoorDash.\n \n You're excited about this opportunity because... \n \n You enjoy solving large-scale machine learning problems that directly impact millions of deliveries.\n You have a strong sense of ownership and enjoy taking models from research through production.\n You're comfortable working in ambiguous environments where experimentation and iteration drive product decisions.\n You care about both model quality and production reliability.\n You're excited to work across a diverse set of ML techniques—from neural networks and optimization to multimodal AI.\n You collaborate well across engineering, product, and data science teams.\n \n We’re excited about you because… \n \n 5+ years of industry experience building and shipping production machine learning systems with measurable business impact (Bachelor's, Master's, or PhD).\n Strong experience developing production machine learning models using modern deep learning frameworks such as PyTorch and distributed data processing technologies such as Spark and Airflow.\n Experience building, deploying, monitoring, and maintaining production ML systems end-to-end.\n Strong software engineering skills in Python and experience with modern ML infrastructure and tooling.\n Deep expertise in at least one of the following areas:\n \n Deep Learning\n Reinforcement Learning\n Optimization / Operations Research\n Large Language Models (LLMs) or Vision-Language Models (VLMs)\n \n Experience applying machine learning to estimation, ranking, prediction, optimization, or decision-making problems at production scale.\n Hands-on experience with LLMs or VLMs is a strong plus.\n Experience in logistics, marketplaces, or delivery platforms is helpful but not required.\n Proficiency using AI-assisted development tools (e.g. Claude Code, Codex, Cursor) throughout the software development lifecycle.\n You are located or are planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA.\n Compensation \n The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.  Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about yo","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","deep-learning","reinforcement-learning","cloud","llm","generative-ai","healthcare","pytorch"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8221807","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:42:26Z","expires_at":"2026-11-13T17:03:28.706911Z","created_at":"2026-10-14T15:25:31.350903Z","updated_at":"2026-10-14T17:03:28.710264Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2bdabd0b-9451-4388-b502-2ba7d839c43f"},{"id":"78fae61b-8780-438a-b75a-b7c5778b3828","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Software Engineer, Machine Learning","slug":"senior-software-engineer-machine-learning-851e39b8","description":"About the Role \n As a Senior Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph at the heart of our fast-growing grocery and retail delivery business.  You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams. We expect Senior Engineers to be able to own projects end-to-end and mentor their junior and mid level peers.\n This role is hybrid with some in-office time expected and will report to an Engineering Manager. \n You're excited about this opportunity because you will... \n \n Develop advanced machine learning models to improve core parts of your teams scope.\n Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.\n Work on creating novel ML \u0026 AI solutions that push both our business and the industry forward.\n Scale our systems and services to fuel the growth of our business.\n Completely disrupt logistics by tackling bleeding-edge, technical problems\n \n We're excited about you because you have... \n \n M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent.\n 5+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.\n Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software\n Experience building data/feature engineering pipelines at scale using Pyspark and Snowflake SQL.\n Experience with building machine learning systems in production by using frameworks such as PyTorch, Keras, lightgbm, scikit-learn, Spark ML, or related.\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).\n \n The national base pay range for this position within the United States, including Illinois and Colorado.\n $167,800 — $246,800 USD \n About DoorDash\n At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.\n Our Commitment to Diversity and Inclusion\n We’re committed to growing and empowering a more inclusive","salary_min":167800,"salary_max":246800,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","healthcare","pytorch","fine-tuning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8143205","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:38:25Z","expires_at":"2026-11-13T17:03:28.716694Z","created_at":"2026-10-14T15:25:31.359543Z","updated_at":"2026-10-14T17:03:28.719518Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/78fae61b-8780-438a-b75a-b7c5778b3828"},{"id":"9b894a7b-e6ce-485c-b095-970a736af6dc","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Machine Learning Engineer, New Verticals Agentic Foundations","slug":"senior-machine-learning-engineer-new-verticals-agentic-foundations-a3f3a5d5","description":"About the Team\n Agentic Foundations, part of New Verticals ML, builds the core AI/ML intelligence that powers high-quality, scalable agents at DoorDash, and proves it through flagship agent experiences such as the Ask grocery assistant. We operate as a closed loop: new models, evals, and representations make our agents better, and real-world agent usage surfaces the gaps that drive our next foundations work. \n About the Role\n We’re looking for a Senior Machine Learning Engineer to join Agentic Foundations with a primary focus on Vertical Agent Development. You will own the continuous improvement of our flagship agents, starting with the Ask Assistant, using an eval-driven loop to make them faster, more cost-efficient, and more reliable for millions of customers. You will also help us bring this approach to new agentic experiences for Merchants and Dashers, turning promising ideas into production-ready agents.\n This is a chance to work at the intersection of LLMs, agents, post-training, and evals on problems that ship. You will partner closely with engineers working on agentic memory, agent-compatible product representations, and post-training of small language models (SLMs), so that what we learn from production agents feeds directly back into our foundations, and what we build there makes our agents better.\n You will report into the engineering lead on our New Verticals AI/ML team. We expect this role to be hybrid with some time in-office and some time remote.\n You’re excited about this opportunity because you will…\n \n Raise the quality of our Consumer agents: build and refine our eval harness-optimization loop to pinpoint failure modes, then iterate on prompts, tools, skills, and context, and measure the impact on real customer tasks.\n Find the best balance of quality, latency, and cost: run rigorous experiments, including fine-tuning open-weights models and deploying small language models (SLMs) where they can replace or augment larger LLMs.\n Launch new agents: take agentic opportunities for Merchants and Dashers from early exploration to production.\n Turn foundations into product impact: work with teammates on agentic memory, agent-compatible product representations, and post-training SLMs for steerable generative recommendation, and bring those capabilities into production agents.\n Shape the roadmap: partner with engineering, product, and business leaders to define an ML-driven strategy for our fast-growing grocery and retail delivery business.\n \n We’re excited about you because you have…\n \n 3+ years of industry ML experience, including hands-on work building and shipping LLM-based agents (tool use, context management, prompting, guardrails) and improving them with evals and data\n Experience with post-training or fine-tuning of open-weights models (e.g., SFT, preference optimization, or RL), ideally including small language models, and sound judgment on quality, latency, and cost trade-offs\n Strong foundation in NLP and machine learning, with proficiency in Python and frameworks such as PyTorch or TensorFlow\n M.S. or PhD in Computer Science, Statistics, Math, or another quantitative field, or equivalent practical experience, plus a collaborative, growth-minded approach and a drive for measurable impact\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).\n \n The national base pay range for this position within the United","salary_min":167800,"salary_max":246800,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","llm","fine-tuning","agents","cloud","pytorch","nlp","healthcare"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8279145","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:38:05Z","expires_at":"2026-11-13T17:03:28.711787Z","created_at":"2026-10-14T15:25:31.355292Z","updated_at":"2026-10-14T17:03:28.714838Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9b894a7b-e6ce-485c-b095-970a736af6dc"},{"id":"634e56a9-b38d-474b-847e-3dc417b38339","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Machine Learning Engineer, Personalization","slug":"staff-machine-learning-engineer-personalization-d2d9e9a7","description":"About the Team \n Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop modern growth and personalization models that power DoorDash's growing retail and grocery business.\n About the Role \n We’re looking for a passionate Applied Machine Learning expert to join our team. As a Staff Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the growth and personalization experiences at the heart of our fast-growing grocery and retail delivery business.  You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories. You will demonstrate a strong command of production level machine learning,  experience with solving end-user problems, and collaborate well with multi-disciplinary teams.\n You will report into the engineering manager on our Personalization team. We expect this role to be hybrid with some time in-office and some time remote (#LI-Hybrid).\n You’re excited about this opportunity because you will… \n \n Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space\n Partner with engineering and product leaders to help shape the product roadmap applying ML\n Mentor junior team members, and lead cross functional pods to create collective impact\n \n You can find out more on our ML blog here \n We’re excited about you because you have… \n \n 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. \n Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software\n M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field\n Expertise in applied ML for  Causal Inference and Recommendation Systems  -  both classical and deep learning based. Additional familiarity with explore/exploit/MAB algorithms \u0026 LLMs is a plus.  \n Machine learning background in Python; experience with PyTorch or TensorFlow preferred.\n Ability to communicate technical details to nontechnical stakeholders\n You keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down\n Desire for impact with a growth-minded and collaborative mindset\n \n \n Data Retention, Privacy \u0026 Bias Audit: Data collected during this process is retained in accordance with our Candidate Privacy Policy and applicable state laws. In compliance with New York City Local Law 144, the independent bias audit summary for Gem is publicly available for review at our Careers Page . \n Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only\n We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.\n The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey \n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","cloud","deep-learning","fine-tuning","healthcare","pytorch","tensorflow","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8225006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:31:26Z","expires_at":"2026-11-13T17:03:28.796671Z","created_at":"2026-10-14T15:25:31.438732Z","updated_at":"2026-10-14T17:03:28.799759Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/634e56a9-b38d-474b-847e-3dc417b38339"},{"id":"501a4fae-853d-480b-9dbb-39daa44f8047","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Machine Learning Engineer, Fulfillment Planning","slug":"staff-machine-learning-engineer-fulfillment-planning-53570b60","description":"About the Team \n The Fulfillment Planning team builds the intelligence that powers DoorDash’s logistics network. We optimize how deliveries are planned and executed across the full delivery lifecycle, improving customer experience, merchant outcomes, Dasher efficiency, and DoorDash profitability.  Our mission is to improve fulfillment quality while reducing fulfillment cost. We do this by applying machine learning, optimization, and systems engineering to the core decisions behind assignment, routing, batching, timing, and fulfillment estimation.\n The team works on some of DoorDash’s most important logistics systems, including:\n \n The core assignment engine that matches deliveries with Dashers in real time.\n Real-time ETA and fulfillment estimation systems for consumers, Dashers, and merchants across diverse geographies and all business lines.\n Assignment and planning algorithms for specialized delivery types, including grocery, retail, parcel, and catering.\n ML models and optimization algorithms that shape demand, improve service quality, and reduce cost.\n Tier-0 logistics services that require high reliability, low latency, and strong operational discipline.\n \n The team also builds reusable ML systems and modeling patterns that scale across DoorDash’s logistics ecosystem. This role will help define the technical direction and best practices for logistics ML at DoorDash.\n About the Role \n We’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of large-scale production ML systems that drive real-time decisioning across DoorDash’s fulfillment ecosystem.\n You will start by owning ML systems for assignment and fulfillment estimation, partnering closely with Product, Data Science, Engineering, and Platform teams to improve delivery quality, cost, and efficiency. Over time, you may also contribute to adjacent areas such as batching, fulfillment execution, demand shaping, and logistics optimization across DoorDash’s business lines.\n This is a high-impact individual contributor role for someone who enjoys building 0→1 ML systems, operating at Staff-level scope, and influencing technical direction across multiple teams. You will define architectures, set modeling and deployment standards, mentor other engineers, and help shape how DoorDash applies machine learning to logistics at scale.\n You’re excited about this opportunity because you will… \n \n Own and build foundational ML systems that directly impact delivery quality, cost, and overall logistics efficiency across DoorDash.\n Work on challenging, real-world machine learning problems , including real-time assignment, routing, and fulfillment estimation.\n Lead 0→1 ML initiatives , defining how machine learning and optimization are applied across fulfillment products.\n Influence architecture, strategy, and execution for a Tier-0 service critical to DoorDash’s logistics platform.\n Collaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.\n Establish best practices for model development, deployment, monitoring, retraining, and governance.\n Define and lead DoorDash’s cutting-edge AI vision for logistics: an LLM-inspired foundation model for intelligence across logistics\n Mentor other engineers and raise the technical bar for logistics ML across the organization.\n \n We’re excited about you because… \n \n You have 8+ years of industry experience building and deploying production-scale machine learning systems.\n You have strong machine learning fundamentals and know how to apply them to large-scale production systems.\n You are fluent in Python\n You have hands-on experience with modern ML frameworks, especially deep learning frameworks.\n You have designed, launched, and operated mission-critical ML models or systems in production, including monitoring, retraining, reliability, and governance.\n You can lead complex technical projects end to end and influence stakeholders across multiple teams or organizations.\n You communicate clearly with both technical and non-technical audiences.\n You are comfortable operating in ambiguous problem spaces and turning 0→1 ideas into production systems.\n You have built or shipped large-scale ML models for recommendation, ads, marketplace, logistics, or other domains.\n You have experience with knowledge distillation from large teacher models into efficient production models.\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares ","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","healthcare","cloud","generative-ai","llm","deep-learning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8224336","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:30:37Z","expires_at":"2026-11-13T17:03:28.79242Z","created_at":"2026-10-14T15:25:31.434336Z","updated_at":"2026-10-14T17:03:28.795093Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/501a4fae-853d-480b-9dbb-39daa44f8047"},{"id":"3fe52aee-b25e-4fe7-bb7c-574f48250345","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Staff Software Architect, Intelligence Systems ","slug":"staff-software-architect-intelligence-systems-715023cb","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril Intelligence Systems (AIS) is focused on positioning Anduril as a lead provider of specialized engineering and next generation national security products for Intelligence Community (IC) customers. We work within the IC to understand their requirements, shape their concepts of operation, and deliver exquisite capability across their problem set. We aim to develop and deploy critically needed capabilities that address our customers’ most pressing national security requirements.\n ABOUT THE JOB\n We are looking for a Software Architect to join our rapidly growing team in Reston, VA. In this role, you will be responsible for defining the architectural direction of large-scale, real-time, mission-critical software. You will lead the design of high-performance systems spanning tactical edge deployments to distributed backend infrastructure, make critical trade-offs between performance, modularity, and maintainability at scale, and mentor senior engineers across the organization. This will require deep expertise in modern C++ and Rust, experience architecting numerics-heavy real-time systems, fluency with asynchronous/multithreaded programming (e.g., Tokio), and a strong grasp of the complex intersection of software and math — including state estimation, target tracking, optimization, and dynamic programming (MCP / Bellman equations) . If you are someone who thrives on ambitious problems, enjoys troubleshooting real-world systems, and wants to build software that is beyond a proof-of-concept — part of real tactical code deployed to the warfighter — then this role is for you. \n WHAT YOU’LL DO \n \n Define and drive the architectural vision for large-scale software systems that ingest, fuse, and act on data from diverse sensors in real time\n Lead the design and implementation of performant, real-time, embedded bare-metal systems in Rust at production scale\n Make high-leverage architectural trade-offs across performance, modularity, testability, and maintainability for mission-critical, edge-deployed systems\n Mentor and technically lead senior engineers, setting coding standards, review processes, and CI/CD best practices across the team\n Engage directly with customers to ensure successful outcomes for mission-critical needs\n Troubleshoot complex, real-world system issues spanning software, math assumptions, sensor behavior, and networking\n Contribute to all phases of the software development lifecycle including prototyping, modeling \u0026 simulation, field testing, and deployment\n Help shape hiring and technical growth of the broader organization as it hyper scales\n \n REQUIRED QUALIFICATIONS\n \n 10+ years of software engineering experience with a Bachelor's degree (or equivalent) in Computer Science, Applied/Computational Mathematics, Electrical Engineering, Aerospace Engineering, Controls/Dynamical Systems, Statistics, or related field\n Proven experience architecting large-scale, production-grade codebases in real-time or high-performance environments\n Experience with modern IPC frameworks and fundamentals\n Experience architecting and designing REST APIs for public consumption to articulate complex real-time systems\n Experience with CI/CD, unit testing, git version control, and microservices\n Currently possesses and is able to maintain an active U.S. Secret clearance.\n \n PREFERRED QUALIFICATIONS\n \n M.S. or Ph.D. in a technical field (dual academic background in software + math highly valued)\n Domain expertise in embedded bare-metal systems\n Expert-level proficiency in modern Rust, including asynchronous and multithreaded programming (e.g., Tokio for Rust)\n Experience with FPGA\n Deep knowledge of networking protocols and systems\n Expertise or experience in cryptographic algorithms and the fundamentals of both symmetric and asymmetric cryptography\n Prior DoD program experience (Army, Air Force, MDA, SCO, Navy)\n Experience with GPU / CUDA kernel development\n \n  \n  \n US Salary Range\n $220,000 — $292,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considera","salary_min":220000,"salary_max":292000,"location":"Reston, VA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","computer-vision","payments","gpu","llm","microservices","api-design"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5261353007?gh_jid=5261353007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:16:39Z","expires_at":"2026-11-13T16:57:16.705084Z","created_at":"2026-10-14T15:21:01.965044Z","updated_at":"2026-10-14T16:57:16.707891Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3fe52aee-b25e-4fe7-bb7c-574f48250345"},{"id":"8bf0267f-9f49-4c14-b3ad-dfe54d410a18","company_id":"1d9e5b7c-1619-4467-a0f1-cee763869454","title":"AI Software Engineer","slug":"ai-software-engineer-c9bf9f69","description":"At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.\n\nSnowflake is building the most powerful AI Data Cloud in the world — and Canada is a critical part of that mission. Our AI/ML engineering teams are delivering the intelligence layer that powers Cortex AI, large language model inference, AI functions, intelligent search, and the next generation of AI-powered experiences on the Snowflake platform.\n\nWe're looking for a Software Engineer — AI to join our growing Toronto engineering team. You'll design, build, and ship AI-powered systems and services that are used by thousands of organizations worldwide. If you're passionate about building production AI infrastructure at scale and want to work alongside world-class engineers on problems that matter, this is the role.\n\n\nAS A SOFTWARE ENGINEER — AI, YOU WILL:\n\n - Design, develop, and ship AI-powered features and services — working across model inference, AI functions, retrieval systems, and intelligent application experiences on the Snowflake platform\n\n - Build production-quality infrastructure for AI workloads — including model serving, embedding pipelines, retrieval-augmented generation (RAG), and AI-driven automation\n\n - Write clean, performant, and well-tested code in languages like Python, Java, C++, or Go — contributing to systems that operate at enterprise scale across Snowflake's multi-cloud infrastructure\n\n - Collaborate with ML researchers, senior engineers, and product managers to translate AI research and product requirements into robust, scalable engineering solutions\n\n - Contribute to system design — participate in design reviews, propose architectural improvements, and help shape the technical direction of AI services\n\n - Own your work end-to-end — from design and implementation through testing, deployment, monitoring, and operational health\n\n - Stay current on AI/ML advancements — evaluate new techniques, models, and tools and assess their applicability to Snowflake's platform and customer needs\n\n - Contribute to a strong engineering culture — through code reviews, documentation, knowledge sharing, and continuous improvement of team practices\n\n\nOUR IDEAL SOFTWARE ENGINEER — AI WILL HAVE:\n\nRequired:\n\n - 3+ years of software engineering experience building production systems, with a strong foundation in computer science fundamentals (data structures, algorithms, distributed systems)\n\n - Experience with AI/ML systems — you've worked on model serving, inference pipelines, LLM integration, embedding systems, or AI-powered application features in a production environment\n\n - Proficiency in one or more of: Python, Java, C++, or Go\n\n - Experience building distributed systems or cloud-native services — you understand the challenges of scale, reliability, and performance in a multi-cloud environment\n\n - Strong problem-solving skills and the ability to break down ambiguous problems into clear engineering tasks\n\n - Collaborative mindset — you work effectively with engineers, researchers, and product managers and communicate your ideas clearly\n\n - Ownership mentality — you take responsibility for your work from design through production and care about quality, reliability, and operational excellence\n\nPreferred:\n\n - Experience with LLM inference, fine-tuning, RAG architectures, or vector search at production scale\n\n - Familiarity with ML frameworks such as PyTorch, TensorFlow, or similar\n\n - Experience with cloud infrastructure (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)\n\n - Background in data platforms, data warehousing, or SQL-based systems\n\n - Experience with CI/CD pipelines, automated testing, and production monitoring/observability\n\n - Contributions to open-source AI/ML projects or published research in AI/ML\n\n\nSNOWFLAKE VALUES WE'RE LOOKING FOR:\n\n - Get It Done — You ship working software. You move fast, iterate, and deliver results — not just prototypes.\n\n - Own It — You take end-to-end responsibility for your code, your systems, and your outcomes. If something breaks, you fix it.\n\n - Make Each Other the Best — You contribute to a culture of learning through thoughtful code reviews, knowledge sharing, and helping teammates grow.\n\n - Think Big — You don't just solve today's problem. You think about how AI at Snowflake should work at 10x scale and buil","salary_min":170000,"salary_max":500000,"location":"Toronto, Canada","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["rag","mlops","pytorch","fine-tuning","cloud","tensorflow","agents","llm"],"apply_url":"https://jobs.ashbyhq.com/snowflake/628f36e0-8554-4d5f-8d5e-a017a761ca54/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T00:00:58.144Z","expires_at":"2026-11-13T16:59:18.383644Z","created_at":"2026-10-14T15:22:50.102644Z","updated_at":"2026-10-14T16:59:18.386616Z","company_name":"Snowflake","company_slug":"snowflake","company_logo_url":"https://www.google.com/s2/favicons?domain=snowflake.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8bf0267f-9f49-4c14-b3ad-dfe54d410a18"},{"id":"08abe8d6-65e3-466e-8f29-1901fbeb8e57","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Software Engineer, Agentic Runtime ","slug":"software-engineer-agentic-runtime-2580af99","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n  \n About the Role: \n  \n The Agentic Runtime team builds the low‑latency, reliable, and secure foundation that powers Glean’s AI agents and assistant experiences at scale. You’ll design and operate core runtime services for multi‑turn orchestration, tool calling, model routing, memory, streaming, and safety. You’ll work across distributed systems, production observability, and ML infra integrations to deliver an experience that feels instant, accurate, and trustworthy — while optimizing cost and reliability. \n  \n You will: \n \n \n Own impactful runtime problems end‑to‑end — from architecture and design to production launch and ongoing reliability. \n Build and evolve core services for session lifecycle, streaming responses (e.g., gRPC/WebSockets), structured tool execution, memory/state, and policy/guardrails. \n Design for performance, correctness, and cost: reduce p50/p95 latency, improve tail behavior, and optimize token/tool budgets. \n Integrate with leading LLM providers (e.g., OpenAI, Anthropic, Google Gemini) and internal evaluation frameworks to improve quality and predictability. \n Harden the platform with fault isolation, retries, timeouts, circuit‑breaking, backpressure, and graceful degradation. \n Instrument deep observability (tracing, metrics, logs) and create playbooks/SLOs for high availability and on‑call excellence. \n Collaborate closely with product, quality, and application teams to prioritize the most impactful roadmap investments. \n \n You are: \n \n \n 3+ years of software engineering experience building production distributed systems or cloud‑native applications. \n BS/BA in Computer Science or related field, or equivalent practical experience. \n Strong coding skills in at least one of: Python, Go, Java, Javascript, Typescript, C++, with a focus on reliability, performance, and tests. \n Product‑minded: you prioritize customer impact, clear SLAs/SLOs, and pragmatic iteration. \n Ownership‑driven with a positive, proactive attitude; comfortable leading projects or learning from battle‑tested engineers. \n \n \n Experience operating services on Kubernetes and at least one major cloud (e.g., GCP, AWS, or Azure). \n Familiarity with event/streaming systems (e.g., Pub/Sub, Kafka), caching (e.g., Redis), and data stores for low‑latency paths. \n Practical understanding of LLM/agents building blocks: tool/function calling, structured outputs, streaming, and model selection/routing. \n Strong observability and debugging skills: tracing (e.g., OpenTelemetry), metrics, dashboards, and production forensics. \n Background in one or more areas is a plus: policy/guardrails, multi‑tenant isolation, rate‑limiting, concurrency control, cost optimization. \n \n Location:   \n \n \n This role is hybrid (4 days a week in our Mountain View office) \n \n Compensation \u0026 Benefits: \n  \n The standard base sa","salary_min":180000,"salary_max":210000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["api-design","agents","llm","distributed-systems","cloud"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4742953005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T23:36:06Z","expires_at":"2026-11-13T16:55:35.324585Z","created_at":"2026-10-14T15:19:25.450729Z","updated_at":"2026-10-14T16:55:35.327737Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/08abe8d6-65e3-466e-8f29-1901fbeb8e57"},{"id":"9cb8cda9-490d-4d6a-9dde-db4aec8490dd","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Tech Lead Manager, AI Evaluations","slug":"tech-lead-manager-ai-evaluations-613503c9","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n About the Role: \n The bottleneck in building reliable and useful AI systems isn’t writing code anymore. It’s knowing what good looks like, applying that knowledge and experience from production usage into building rigorous evals, and using those evals to guide continuous product self-improvement loops. \n As the Tech Lead Manager of AI Evaluations, you will lead a team of applied AI scientists and engineers and build the evaluation strategy and platform that helps Glean ship delightful and reliable AI experiences. You will make evaluation a continuous part of how we develop and operate models, harnesses, assistants, agents, and other AI products at Glean. \n You’ll guide the team in translating emerging AI/ML research into reliable evaluation systems, build scalable, efficient and reusable eval infrastructure and trusted quality signals, and work across R\u0026D, product, and marketing teams to turn evaluation results into better products and customer outcomes. \n You will: \n \n Own the AI evaluation eng roadmap and technical direction end to end: from defining what success means and building the evaluation platform to integrating results into release and product decisions. \n Build scalable, reusable evaluation infrastructure for datasets, experiments, graders, trace capture and replay, result analysis, and dashboards. Make evaluations reproducible, versioned, cost-aware, and easy for product and engineering teams to use. \n Create and maintain representative evaluation sets from expert-curated examples, appropriately governed production signals, synthetic cases, and historical failures. Cover common workflows, edge cases, long-tail requests, adversarial inputs, and important user and domain slices; protect held-out acceptance sets from tuning leakage. \n Define a balanced quality measurement system for AI products, including correctness, groundedness, retrieval and context relevance, completeness, instruction following, citation quality, user preference, and task success. For agents, evaluate tool selection and arguments, multi-step trajectories, policy compliance, recovery, and final task state, not just the final response. \n Develop a fit-for-purpose mix of deterministic checks, model-based graders (including LLM-based autograders), and human evaluation. Establish clear rubrics; validate and calibrate automated judges against human judgments; and measure evaluator reliability and limitations so teams can trust and interpret scores. \n Integrate evaluation into development and operations: fast CI regression checks, broader pre-release suites, model and prompt comparisons, and sampled production evaluation. Build feedback loops from user feedback and production traces into new test cases, and use monitoring, canaries, and experiments to detect regressions and drift. \n Make quality tradeoffs measurable by connecting evaluation","salary_min":250000,"salary_max":350000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","llm","distributed-systems","alignment","agents","generative-ai","evaluation"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4742957005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T22:27:22Z","expires_at":"2026-11-13T16:55:35.432797Z","created_at":"2026-10-14T15:19:25.54086Z","updated_at":"2026-10-14T16:55:35.435547Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9cb8cda9-490d-4d6a-9dde-db4aec8490dd"},{"id":"fad93271-34c1-404a-b2f3-8bc475aaf06a","company_id":"7f631da3-2c29-4575-a413-a9ed92f8af53","title":"Senior AI Engineer, Agentic Systems","slug":"senior-ai-engineer-agentic-systems-1274f235","description":"About the team: \n Rubrik secures and accelerates the world’s AI transformation. As AI agents reshape the enterprise, Rubrik’s Enterprise AI Incubation team proves it on Rubrik itself. We are building a thinking enterprise: applications that don't just record the business but help run it. They learn from our data, act through our own agents, and improve with every decision. Fully backed by executive leadership, this team drives meaningful, large-scale enterprise transformation.\n About the role:\n We want senior engineers who have already shipped agents that real people rely on, and who are ready to do it again at higher stakes. You will drop into the real work, redesign it around agents that carry it end to end, and ship it as the new way that part of Rubrik operates.You’ll own your agent systems end to end: understanding the workflow, designing the architecture, writing the code, deploying, and running it in production. Rather than simply querying an API, you engineer robust, production-grade infrastructure around model endpoints, integrating custom tooling, context pipelines, automated evaluations, and defensive guardrails to ensure resilience against unstructured real-world data.\n You also decide whether a problem needs an agent, a simpler automation, or nothing at all, and you have explicit authority to stop or re-scope work that won’t deliver impact. You thrive in ambiguous environments with a low-ego mindset, leveraging AI coding tools as core collaborative partners in your engineering workflow.\n What you’ll do:\n \n Lead product discovery alongside Product Managers and domain experts to understand real workflows, map them out, and define clear problems, baselines, and success criteria as the foundation for building agentic solutions.\n Design, build, test, and deploy production agents, automations, and internal tools using coding agents, LLM APIs, and agent frameworks, integrated with Rubrik’s internal agent platform and business systems.\n Turn complex processes into multi-agent workflows that carry real work and make decisions: orchestrators that qualify and routes deals, workers that move orders through approval and fulfillment under business rules, agents that monitor signals and recommend actions for customer health, or coordinated agents that handle hire-to-retire steps across HR, IT, and managers with shared state and clear handoffs.\n Engineer agents for autonomy with reliability, including tool and orchestration flows, context management, caching, retries, and failure handling.\n Leverage full-stack engineering across backend services, APIs, data models, interactive screens, approval UIs, and chat interfaces as the complete medium to deliver high-ownership, user-facing agent systems.\n Apply solid software engineering practices to AI systems, treating prompts, skills, configs, and specs as versioned artifacts, with code review, tests, CI or CD, and staged rollouts.\n Implement evaluation, guardrails, and quality control: derive evals from workflow data, establish quality gates and guardrails, integrate human-in-the-loop approvals where needed, and monitor production runs to refine agents over time.\n Use measured results to decide how to evolve or retire agents, and turn successful systems into patterns and libraries that can be reused.\n \n Experience you’ll need:\n \n Around 7 or more years of professional software engineering experience in production systems, and around 2 or more years of professional, hands-on experience building AI agents and agent powered production applications with measurable outcomes.\n Strong full stack engineering background, with a track record of designing, building, and owning services end to end, including backend APIs and integrations, data models, and user facing interfaces such as approval UIs, dashboards, or chat surfaces.\n A builder mindset: comfortable defining baselines and metrics, reporting results in business terms, working in a fast moving environment, and closing the loop by building, demoing, learning, and building again. If you like seeing improvements in hours saved, errors avoided, and teams unblocked, you will have plenty of chances to measure that here.\n \n Software engineering skills and best practices:\n \n System design: break down complex problems, design APIs and data models, reason about latency, throughput, and failure modes, and choose simple, robust architectures.\n Algorithms, data structures, access control permissions, and data provenance.\n Spec driven development: turn vague requirements into clear problem statements, write or refine design docs, and use a Spec → Plan → Task → Code→ Converge flow so work is traceable from design to code, including when you use AI coding agents.\n Execution discipline: use version control, code review, automated tests, CI or CD, staged rollouts and rollbacks, logging, metrics, and tracing, and improve systems based on issues and signals from production.\n \n AI engineering skills and best practices","salary_min":188500,"salary_max":282700,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","cloud","api-design","agents","fine-tuning"],"apply_url":"https://www.rubrik.com/company/careers/departments/job.8274601?gh_jid=8274601","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T17:15:42Z","expires_at":"2026-11-13T17:03:40.183779Z","created_at":"2026-10-14T15:25:42.354845Z","updated_at":"2026-10-14T17:03:40.186843Z","company_name":"Rubrik","company_slug":"rubrik","company_logo_url":"https://www.google.com/s2/favicons?domain=rubrik.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fad93271-34c1-404a-b2f3-8bc475aaf06a"},{"id":"30f0bfd5-b030-48f6-9124-0c1234f28ba7","company_id":"31ae48bc-c938-4c26-a348-0bf3c089a446","title":"Staff Product Manager, AI Inference","slug":"staff-product-manager-ai-inference-85275e80","description":"CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at  www.coreweave.com . \n About the Team \n As the Staff Product Manager - AI Inference, you will lead CoreWeave's strategic efforts in shaping and developing cutting-edge AI inference services that drive innovation and business outcomes for our customers. You will collaborate closely with engineers, designers, and industry partners to create world-class products that empower organizations to build, deploy, scale, and optimize AI models and applications efficiently and effectively.\n The ideal candidate is passionate about AI and cloud technologies, with a deep understanding of the foundation model architectures, AI inference landscape, AI application ecosystem, cloud-native technologies, and the competitive landscape. You will leverage market insights and technical expertise to define the product vision, roadmap, and go-to-market strategy, ensuring that CoreWeave builds on its market-segment position as the leading AI Hyperscaler.\n Key Responsibilities: \n \n Product Vision and Strategy: Help refine the product strategy for AI application cloud services aimed at foundational model Inference, along with focus on optimization across the entire CoreWeave product portfolio for AI workloads. Solve novel problems related to scaling AI model inference on specialized hardware.\n Roadmap Development: Own the product roadmap for AI inference services, balancing near-term customer needs with long-term vision, to deliver differentiated and scalable AI cloud services.\n AI and Cloud Expertise: Stay current on advancements in AI/ML technologies including inference engines, model serving architectures, cloud infrastructures, and software development methodologies to inform product decisions and foster innovation.\n Define product portfolio: Manage ambiguity and complexity of a fast evolving AI landscape to define new product investments and develop a portfolio of inference capabilities that deliver long-term differentiation and customer value.\n Customer Engagement: Collaborate with key customers to understand their AI workloads, pain points, and future requirements to continuously improve our service offerings.\n Cross-functional Leadership: Collaborate with engineering, sales, marketing, and customer success teams to ensure seamless product development and deployment.\n Market Analysis: Analyze market trends, customer feedback, and the competitive landscape to identify growth opportunities and ensure CoreWeave stays ahead of industry trends.\n Go-to-Market Strategy: Partner with industry partners, marketing, and sales teams to develop and execute effective go-to-market strategies for AI cloud services, including pricing strategies, positioning, messaging, and competitive differentiation.\n \n Qualifications: \n \n Experience: 8+ years of experience in product management, with at least 5 years in the cloud services or AI/ML market segment.\n Technical Knowledge: Hands on practitioner and deep understanding of AI/ML workloads including foundation model inference, inference engines such as vllm, SGLang, TensorRT-llm, and llm-d, inference optimization techniques such as quantization and speculative decoding, cloud infrastructure (GPUs), and cloud-native architectures (Kubernetes, microservices).\n Leadership: Proven ability to lead cross functional teams, with strong decision-making, project management, and mentoring skills.\n Customer-Centric Approach: Demonstrated experience working closely with customers to identify needs and translate them into product features and solutions.\n Communication Skills: Excellent verbal and written communication skills with the ability to influence cross-functional teams and stakeholders.\n Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. MBA or equivalent experience is a plus.\n Visionary Leadership: Ability to think strategically while being able to dive into technical details to guide the product team.\n Results-Oriented: Proven track record of driving business growth through innovative product solutions in the AI and cloud space.\n \n Why CoreWeave? \n At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:\n \n Be Curious at Your Core\n Act Like an Owner\n Empower Employees\n Deliver Best-in","salary_min":207000,"salary_max":275000,"location":"Sunnyvale, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["microservices","mlops","cloud","generative-ai","llm","inference"],"apply_url":"https://coreweave.com/careers/job?4720733006\u0026board=coreweave\u0026gh_jid=4720733006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T14:43:58Z","expires_at":"2026-11-13T16:56:02.427193Z","created_at":"2026-10-14T15:20:12.017713Z","updated_at":"2026-10-14T16:56:02.430397Z","company_name":"CoreWeave","company_slug":"coreweave","company_logo_url":"https://www.google.com/s2/favicons?domain=coreweave.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/30f0bfd5-b030-48f6-9124-0c1234f28ba7"},{"id":"0e915c96-e091-4d28-9652-01f3efa478ae","company_id":"f5ee7284-a657-4da2-b351-cb806a3681cd","title":"Infrastructure Security Engineer (Bare Metal \u0026 Platform)","slug":"infrastructure-security-engineer-bare-metal-platform-65c20bb1","description":"SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.\n ABOUT THE ROLE: \n We are seeking a hands-on Infrastructure Security Engineer to build and secure SpaceXSI's infrastructure from the bare-metal layer up through the platform and application stack. In this role, you will design, implement, and harden physical and private-cloud foundations—servers, networks, identity, and orchestration—and carry that security posture into containers, automation, and hybrid connectivity with public cloud.\n This role focuses on securing critical infrastructure spanning data centers, colo, and hybrid environments, with work that may span platforms such as SpaceXSI, X Social, X Money, and related systems. You’ll operate with an automation-first mindset: building secure foundations at the metal and OS layer, hardening platforms at scale, and partnering closely with engineering so security is embedded in how we build and run systems—not bolted on after the fact.\n RESPONSIBILITIES: \n Bare metal, data center \u0026 network security\n \n Design and implement secure bare-metal and private-cloud architectures (servers, storage, out-of-band management, BIOS/UEFI/BMC firmware posture)\n Harden physical and virtual fleets: OS baselines (Linux/Windows), CIS benchmarks, patch and vulnerability management, and secure boot / measured boot where applicable\n Hands-on firmware, BMC/iDRAC/iLO, PXE/Kickstart provisioning, and hardware lifecycle security\n Build and secure network foundations: segmentation, load balancers, DNS, PKI, NAC, and IDS/IPS on real hardware\n Own hybrid connectivity between on-premises and cloud (site-to-site VPN, Direct Connect / Interconnect / ExpressRoute, SD-WAN, zero-trust access)\n Manage identities and privileged access across Active Directory / LDAP / Kerberos and cloud IAM (federation, SAML/OIDC, PAM)\n Assist with security assessments and audits of physical, on-premises, and hybrid infrastructure\n Monitor and remediate infrastructure to comply with regulations and best practices (e.g., PCI, NIST CSF, GDPR, HIPAA)\n \n Platform, containers \u0026 developer enablement\n \n Design and implement secure container and Kubernetes standards on bare metal and private cloud (not only managed EKS/GKE/AKS), including RBAC, network policy, and secrets\n Develop and maintain Infrastructure as Code and configuration management—especially Puppet—with embedded security controls for physical and virtual fleets\n Collaborate with development teams so security best practices are integrated into CI/CD pipelines\n Secure and enhance CI/CD pipelines; integrate and maintain code and image scanning platforms\n \n Detection, operations \u0026 tooling\n \n Monitor and respond to security events and incidents spanning bare metal, network devices, hosts, and hybrid cloud\n Maintain SIEM data pipelines that ingest on-premises network, host, and cloud telemetry for reliable alerting\n Build, deploy, and maintain security operations infrastructure using Python, Terraform, and Puppet\n Develop dashboards and alerts from security metrics across physical and platform layers\n Develop and maintain infrastructure security policies, standards, and procedures from metal through platform\n Own security projects end to end: identify issues and implement solutions\n Stay current with emerging threats and mitigations for bare-metal, firmware, network, and hybrid-cloud infrastructure\n \n BASIC QUALIFICATIONS: \n \n Bachelor's degree in Computer Science, Cybersecurity, or a related field\n 3–5 years of experience in infrastructure security, platform security, or related hands-on roles\n Proven experience securing bare-metal, data-center, or private-cloud environments (not cloud-only resumes)\n Hands-on experience with firmware, BMC/iDRAC/iLO, PXE/Kickstart provisioning, and hardware lifecycle security\n Strong proficiency with Puppet for configuration management and fleet hardening in production\n Strong understanding of network security concepts and protocols, including hands-on work with firewalls, segmentation, and hybrid connectivity\n Experience with hybrid identity (AD/LDAP or similar) integrated or federated with cloud IAM\n Experience with Infrastructure as Code (e.g., Terraform) applied to physical or VM fleets\n Familiarity with containerization ","salary_min":100000,"salary_max":258000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["payments","cloud","data-pipeline","security","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/xai/jobs/5262880007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-10T01:45:54Z","expires_at":"2026-11-13T16:55:31.592515Z","created_at":"2026-10-14T15:19:21.532282Z","updated_at":"2026-10-14T16:55:31.595612Z","company_name":"xAI","company_slug":"xai","company_logo_url":"https://www.google.com/s2/favicons?domain=x.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0e915c96-e091-4d28-9652-01f3efa478ae"}],"page":1,"per_page":20,"total":1853,"total_is_exact":true,"total_pages":93}