{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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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":"12e81e2e-7f84-4b3e-8fc0-0b66e2fcdb45","company_id":"a0000000-0000-0000-0000-000000000001","title":"Engineering Manager, Claude Platform","slug":"engineering-manager-claude-platform-cc593300","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n Developers and enterprises build on Claude through the Claude Platform. Our models are getting exponentially more intelligent, and our APIs and developer tools need to evolve just as quickly so developers can take advantage of that intelligence safely.\n We're hiring Engineering Managers to lead teams that build these APIs and developer tools. We are shipping APIs and infrastructure for building and running agents in production. These APIs ship alongside SDKs, docs, and tooling that developers (and agents!) utilize in order to build high quality integrations. These abstractions are backed by our identity, verification, and trust platform, which lets us scale access to Claude responsibly.\n Key responsibilities\n \n Lead a team of engineers to ship high quality work quickly, owning planning, prioritization, delivery, and operational health\n Partner with product to set your team's roadmap, and bring a strong point of view on what developers need\n Talk to customers directly and turn what you learn into engineering priorities\n Guide API design and architecture decisions for distributed systems that have to stay reliable as usage grows\n Work closely with Research, Safeguards, Security, and go-to-market teams to bring new model capabilities to developers safely\n Recruit, coach, and grow strong engineers\n \n Minimum qualifications\n \n You have experience managing high-performing software engineering teams shipping developer products, including hiring, coaching, and performance management\n You're product-minded and customer-oriented. You care about who uses what your team builds, and you've shaped roadmaps alongside product partners\n You've built and scaled distributed systems in production, and you have the technical depth required to guide architecture and API design\n You've led teams that ship quickly and hold a high quality bar\n You collaborate well across functions and can align teams you don't manage\n You care about Anthropic's mission and about developing AI safely\n \n Preferred qualifications\n \n Experience building agent infrastructure or products on top of LLMs\n Experience with identity, verification, access control, or trust and safety systems\n \n Deadline to apply:  None. Applications will be reviewed on a rolling basis. \n Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. \n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $405,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before you","salary_min":405000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["api-design","distributed-systems","llm","alignment","platform"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5378643008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-14T04:15:36Z","expires_at":"2026-11-13T16:54:55.457822Z","created_at":"2026-10-14T15:17:21.754142Z","updated_at":"2026-10-14T16:54:55.461135Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/12e81e2e-7f84-4b3e-8fc0-0b66e2fcdb45"},{"id":"2b1514f0-20bf-4830-9fdc-23e5c0f8bbed","company_id":"a25140f5-772d-4c47-947d-7c655ed80737","title":"Senior Software Engineer - Normalization Platform","slug":"senior-software-engineer-normalization-platform-451aa2a7","description":"Senior Software Engineer - Normalization Platform \n Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . \n This position is based out of our headquarters in the Greater Seattle area.  #LI-hybrid \n Who We Need   \n Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. We are seeking candidates inspired by the opportunity to apply data in the development of real-world health solutions. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference.     \n If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.  \n This Opportunity   \n Truveta's mission is Saving Lives with Data: helping researchers find cures faster, empowering every clinician to be an expert, and helping families make the most informed decisions about their care. Semantic normalization is where that data becomes usable. Health systems describe the same diagnosis, lab result, or medication in countless ways, and our platform maps each one to a standard medical concept, so researchers can study data from many health systems as one. Every dataset Truveta delivers runs through it.   \n As a Senior Software Engineer, you will own major pieces of the platform's next-generation architecture. You will scale the service for both the volume and the variety of its workloads, building a flexible system that keeps pace with Truveta's growing data volume and expanding range of data sources.   \n We are seeking backend engineers who: \n \n \n Have proven experience building reliable, secure, and scalable software solutions using modern cloud-based paradigms   \n Are quick learners who can iterate on and evolve distributed software solutions while carefully balancing privacy, security, and reliability requirements with a changing product landscape   \n Have knowledge of and experience designing and working with distributed systems, data pipelines, and APIs   \n Can guide workstreams, mentor and inspire junior developers, and cultivate a positive work environment   \n Adhere to Truveta principles in support of ethical innovation   \n Are committed to ongoing training on key topics such as privacy, ethics, and security   \n \n Key Qualifications:   \n \n 5+ years of experience building production-quality software in a team setting   \n Experience building cloud services or data pipelines in Java, Python, or C#   \n Experience building and supporting cross-platform, multi-tenant services   \n 2+ years of experience on cloud-native platforms (AWS, GCP, or Azure)   \n B.S. or M.S. in Computer Science or a related field   \n InfraOps or DevOps experience is a plus   \n Kubernetes experience is a plus   \n Healthcare domain experience is a plus   \n Experience with AI agents is a plus   \n \n Why Truveta? \n Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together. \n We Offer: \n \n Interesting and meaningful work for every career stage \n Great benefits package \n Comprehensive benefits with strong medical, dental and vision insurance plans \n 401K plan \n Professional development \u0026 training opportunities for continuous learning \n Work/life autonomy via flexible work hours and flexible paid time off \n Generous parental leave \n Regular team activities (virtual and in-person) \n The base pay for this position is $155,000 to $190,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options. \n \n If you are based in California, we encourage you to read this important information for California residents linked here. \n Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disprop","salary_min":155000,"salary_max":190000,"location":"Seattle, WA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","healthcare","distributed-systems","data-pipeline","platform"],"apply_url":"https://job-boards.greenhouse.io/truveta/jobs/6223732004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T23:29:02Z","expires_at":"2026-11-13T17:00:07.879355Z","created_at":"2026-10-14T15:23:39.300558Z","updated_at":"2026-10-14T17:00:07.882558Z","company_name":"Truveta","company_slug":"truveta","company_logo_url":"https://www.google.com/s2/favicons?domain=truveta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2b1514f0-20bf-4830-9fdc-23e5c0f8bbed"},{"id":"fcb2f68d-9ea2-439d-9d09-29431b4bdeec","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Machine Learning Engineer - Gen SWE","slug":"machine-learning-engineer-gen-swe-049769f2","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n This role follows a hybrid work schedule and reports to a Software Tech Lead Manager.\n You will: \n \n \n Own and drive the roadmap for ML-powered pickup and dropoff features, from problem definition through launch, in partnership with PM, UX, data science, and other commercialization engineering teams\n \n Train, evaluate, and deploy ML models for occupancy detection, rider-vehicle interactions, pullover selection, and lost and found\n \n Design fallback systems that cascade between onboard and offboard models based on latency, confidence, and connectivity\n \n Build distributed systems that span vehicles, cloud services, and rider apps, and that handle intermittent and inconsistent connectivity well\n \n Work across the stack (data pipelines, model serving, backend services, and client integration) to ship end-to-end, user-facing features\n \n Define success metrics and use offline evaluation, simulation, and live experiments to measure impact on service quality and rider experience\n \n You have: \n \n \n BS degree in Computer Science or equivalent practical experience\n \n 5+ years of software engineering experience, including building and deploying ML models into production\n \n Experience building backend distributed systems\n \n We prefer: \n \n \n Experience with C++\n \n MS in Computer Science, or equivalent practical experience\n \n Experience in developing machine learning models, infrastructure, and pipelines\n \n Experience deploying models on-device or on edge hardware with compute and latency constraints\n \n Track record of owning ambiguous, user-facing problems end-to-end and setting your own technical direction\n \n Experience in autonomous vehicles or robotics\n \n Disclosure for WA Based \u0026 Remote Roles: \n In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:\n Health, dental, vision, life, disability insuranceRetirement Benefits: 401(k) with company matchPaid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employmentSick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year\n US Remote Only: Please note that Waymo may not be able to employ remotely in all US locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.\n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $213,000 — $263,000 USD","salary_min":213000,"salary_max":263000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["mlops","distributed-systems","data-pipeline","autonomous-vehicles","robotics","machine-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8212440","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T13:20:32Z","expires_at":"2026-11-13T16:55:54.938681Z","created_at":"2026-10-14T15:20:04.385328Z","updated_at":"2026-10-14T16:55:54.941384Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fcb2f68d-9ea2-439d-9d09-29431b4bdeec"},{"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":"6aceb6c9-aa17-4cd3-81ca-d26284538246","company_id":"5b08d89d-9846-4ef7-8b53-d07ef3ee6c19","title":"Software Engineer, ML Infrastructure","slug":"software-engineer-ml-infrastructure-f2fd5868","description":"About Arc Institute \n Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.\n Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.\n Our two Institute Initiatives reflect this model in action:\n \n Virtual Cell Initiative : Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.\n Alzheimer's Disease Initiative : Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.\n \n More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.\n About the position \n You'll join Arc's Infrastructure Engineering team and own the data and evaluation of ML infrastructure for Arc's virtual cell models. You'll start with two systems: our Model Performance Dashboard, which benchmarks those models, and the pipeline that turns single-cell data into their training sets. You'll set the technical direction for both and connect them, so every new dataset version is judged by what it does to the models. Later in your first year, the role widens into the engineering that makes the ML team's training and evaluation run fast and at scale, lab-in-the-loop infrastructure, validation frameworks for agent-written software, and Arc's rules for what research data we bring in, keep and share. The role consolidates ownership that is split across several teams today. \n Why this position could be the best job you’ve ever had \n \n You will contribute to building a virtual cell. Your evals show which data makes Arc's models better, and the answer shapes which experiments Arc's labs run next.\n You will own the platform end to end, and you work directly with the ML researchers and scientists who rely on it.\n \n About you \n \n You finish what you own, and you fix what's broken without being asked.\n You're curious about the biology, enough to learn single-cell perturbation data and argue about what an eval should measure. \n You're steady when priorities shift. Research is high-risk, so you test ideas early and change course when the evidence says to.\n You don't wait on scarce expert time. If proving a dataset's value means running the model evals yourself, you run them.\n \n In this position you will \n \n Own how Arc measures the performance of its virtual cell models, starting with the backend of our Model Performance Dashboard, which you'll take over within your first two months. \n Decide with the ML team which evaluation tools they need, then design and build them so researchers can evaluate and compare models themselves, and measure what each dataset version does to model performance.\n Redesign the pipeline that turns single-cell data into training sets for our virtual cell models, then run it with AI agents: agents find, process and curate datasets, and automated quality checks, not manual review, decide whether a dataset version is ready for model training.\n Own the lab-in-the-loop infrastructure that turns model performance results into the case for what Arc's labs should test next, working directly with the science leads who design those experiments . \n Build or buy validation frameworks (tests, evals, QC gates, policies) that let agent-written code and apps ship without line-by-line human review. Start with our team, where you'll also own how we work with coding agents, then extend them to apps that scientists across Arc build themselves.\n Own the engineering that makes the ML team's training and evaluation run fast, reliably and at scale. The ML team owns the research and the models. Once a model is ready to push, it enters the train-and-eval CI system you own, which feeds our Model Performance Dashboard. You'll also make multi-node training a supported path, track down distributed-training failures, and measure and raise throughput and GPU utilization (MFU) on clusters that Arc IT operates.\n \n Requirements \n \n Bachelor’s degree with 8 years of relevant experience, or Master’s degree with 6 years of relevant experience.\n You've owned a production data or ML platform that researchers depend on, end to end (pipelines, storage, versioning), and set its technical direction.\n You design and build systems with AI tools and agents, and you make their output verifiable with evals, QC gates or tests before anyone relies on it.\n ","salary_min":191000,"salary_max":237000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","healthcare","pytorch","distributed-systems","agents","machine-learning","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/arcinstitute/jobs/6222681004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T22:16:26Z","expires_at":"2026-11-13T17:03:53.841883Z","created_at":"2026-10-14T15:25:57.647484Z","updated_at":"2026-10-14T17:03:53.845803Z","company_name":"Arc Institute","company_slug":"arc-institute","company_logo_url":"https://www.google.com/s2/favicons?domain=arcinstitute.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6aceb6c9-aa17-4cd3-81ca-d26284538246"},{"id":"3b73d4e3-8873-4465-bf7b-ec795560a17b","company_id":"7455e78c-482b-4f7b-9d62-11b78645818a","title":"Software Engineer 2 - Development Infrastructure ","slug":"software-engineer-2-development-infrastructure-3dfd6ec0","description":"About the Role\n Abnormal AI empowers businesses of all sizes to combat cybercrime through our innovative cloud products. To achieve our mission, we're building a suite of interconnected security solutions on a unified platform, designed to operate flawlessly in global data centers.\n The Development Infrastructure team plays a critical role in multiplying the impact of our product teams. We create an environment that fosters high-quality software development, and engineering excellence. This team has become instrumental in the success of our engineering organization.\n You are someone who:\n \n Thrives in a collaborative, fast-paced environment\n Possesses a passion for helping others build world-class systems\n Demonstrates exceptional teamwork skills\n Embraces continuous learning and enjoys tackling complex problems\n \n What you will do \n \n Lead the design and delivery of complex, multi-component features and systems of the Development Infrastructure team's offerings, and shape the roadmap for this area.\n Develop and maintain CI/CD infrastructure and tools for Engineering to develop and ship their changes reliably with less effort.\n Design and implement enhancements to GHA infrastructure, base Docker images and build/deploy pipelines with improvements in scalability, performance and costs.\n Use AI tools to explore and compare solutions, and adapt the generated changes to real production constraints, weighing system complexity and long-term maintainability.\n Take ownership of on-call issues, including complex issues where the root cause is unclear, and fix the systemic gaps behind them.\n Participate in planning, code reviews, standups, and other aspects of the software development life cycle, and coach other engineers on the team.\n \n Must Haves\n \n 3+ years of professional experience as a hands-on engineer building backend systems and/or platforms.\n 2+ years of experience working with Python.\n Experience delivering complex projects end-to-end in a cloud native environment.\n Experience building or operating CI/CD, build, or deployment systems in production, including on-call and incident response.\n Understanding of distributed systems, containerization and microservices.\n Practical experience using Generative AI tools in day-to-day engineering workflows.\n \n Nice to Haves\n \n Experience creating and maintaining CI/CD systems.\n Experience with GitHub Actions.\n Experience with Go.\n Experience with Bazel.\n Experience working on or with teams like “Engineering Effectiveness”, “Engineering Productivity”, “Development Experience”, “Development Infrastructure” or similar.\n Knowledge of Docker, Kubernetes, or similar technologies.\n Familiarity with Generative AI tools such as Codex and Claude, and experience driving AI-first workflows and solutions.\n \n  \n #LI-ML1\n Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.\n Base salary range:\n $149,200 — $214,500 USD \n A note on AI in our process:  Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.\n Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here . If you would like more information on your EEO rights under the law, please  click here .","salary_min":149200,"salary_max":214500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["generative-ai","microservices","distributed-systems","infrastructure"],"apply_url":"https://abnormal.ai/careers/jobs/8015189003?gh_jid=8015189003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T23:40:56Z","expires_at":"2026-11-13T16:55:40.593701Z","created_at":"2026-10-14T15:19:46.257997Z","updated_at":"2026-10-14T16:55:40.597796Z","company_name":"Abnormal Security","company_slug":"abnormal-security","company_logo_url":"https://www.google.com/s2/favicons?domain=abnormalsecurity.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3b73d4e3-8873-4465-bf7b-ec795560a17b"},{"id":"034aa435-5a12-4679-b2f5-4b3edc0913d3","company_id":"3da82454-107f-427f-88e7-01f315ef93fb","title":"Member of Technical Staff - Production Engineering","slug":"member-of-technical-staff-production-engineering-7a9b3195","description":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: infrastructure and tools that help ambitious AI teams train, evaluate, and deploy advanced models.\n\n\n\n\nROLE IMPACT\n\nPlatform engineering at Prime Intellect sits on the path from a research idea to a running AI workload. Your core mandate is to make every engineering team faster and safer: turn recurring infrastructure and security needs into paved roads, self-service capabilities, and guardrails that help teams move from idea to production with confidence.\n\nThis is a hands-on senior role with broad technical ownership. You will write code, set platform standards, and partner directly with research, product engineering, and security to improve how services are built, shipped, and operated.\n\n\n\n\nWHY THIS ROLE STANDS OUT\n\n - Work at the intersection of cloud infrastructure and distributed, GPU-intensive AI workloads\n\n - Own foundational systems in a small, senior team where technical decisions have visible impact\n\n - Multiply the impact of other teams through secure defaults, automation, and a strong developer experience\n   \n   \n\n\nWHAT YOU’LL OWN\n\n - Build reusable infrastructure-as-code and reliable CI/CD workflows for platform services\n\n - Design cloud foundations spanning compute, networking, identity, secrets, and service delivery\n\n - Develop progressive rollout, health-check, and rollback patterns for critical infrastructure\n\n - Build self-service platform capabilities, templates, and guardrails that shorten the path from code to production\n\n - Partner with research and product teams to remove delivery bottlenecks and turn recurring needs into reusable platform capabilities\n\n - Define practical observability standards across metrics, logs, dashboards, and alerting using tools such as Grafana\n\n - Define and own platform SLOs, partnering with service teams on targets, error budgets, and reliability priorities\n\n - Turn security and compliance requirements into reusable platform controls\n\n - Lead complex platform projects from technical design through adoption and steady-state operation\n   \n   \n\n\nWHAT WE’RE LOOKING FOR\n\n - 5+ years in infrastructure, platform, or security-focused engineering\n\n - Deep hands-on experience with Terraform or similar infrastructure-as-code tooling\n\n - Strong knowledge of cloud networking, IAM, secrets management, and CI/CD\n\n - Experience designing secure software delivery lifecycle environments from development through production\n\n - Production experience with Kubernetes or similar container orchestration platforms\n\n - Ability to debug across infrastructure layers and make sound trade-offs under ambiguity\n\n - Clear technical communication and a track record of leading cross-functional projects\n   \n   \n\n\nNICE TO HAVE\n\n - Experience operating ML/LLM training or inference infrastructure\n\n - Exposure to GPU infrastructure and distributed systems\n\n - Experience with zero-trust access patterns\n\n - Experience supporting compliance or audit-readiness programs\n\n\n\n\nWHAT WE OFFER\n\n - Cash compensation $150K–$300K with significant equity\n\n - Flexible work arrangement (remote or San Francisco office)\n\n - Full visa sponsorship and relocation support\n\n - Professional development budget for courses and conferences\n\n - Regular team off-sites and conference attendance\n\n\n\n\nGROWTH OPPORTUNITY\n\nYou’ll have direct influence over the platform behind open frontier AI research and products used by ambitious AI teams. Your impact will show up in faster delivery, safer operations, and less infrastructure work repeated across teams. We value ownership, technical judgment, and engineers who turn complex problems into simple, durable systems.","salary_min":150000,"salary_max":300000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","llm","cloud","gpu"],"apply_url":"https://jobs.ashbyhq.com/PrimeIntellect/ae969ec1-0f44-4289-9797-a880b05db389/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T22:36:11.481Z","expires_at":"2026-11-13T16:58:27.6209Z","created_at":"2026-10-14T15:22:06.001502Z","updated_at":"2026-10-14T16:58:27.62379Z","company_name":"Prime Intellect","company_slug":"PrimeIntellect","company_logo_url":"https://www.google.com/s2/favicons?domain=primeintellect.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/034aa435-5a12-4679-b2f5-4b3edc0913d3"},{"id":"add4fc69-019a-44ed-84cb-02a73f033485","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Senior Software Engineer, Backend/Fullstack (Coinbase Advisor - Agentic Trading)","slug":"senior-software-engineer-backendfullstack-coinbase-advisor-agentic-trading-dcaad948","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n Senior Software Engineer, Backend/Fullstack (Coinbase Advisor - Agentic Trading)\n We're hiring a Senior Software Engineer to join the Coinbase Advisor team within the Consumer \u0026 Business group. Coinbase Advisor is the world's first RIA-licensed agentic trading system: an AI advisor living inside the Coinbase app that holds a natural conversation about a user's portfolio, gives personalized financial advice, and executes trades on their behalf. This role is primarily backend on a full-stack team. You'll own the services that make agentic trading feel fast, clear, and trustworthy for millions of customers.\n What you'll do: \n \n Own backend services powering Coinbase Advisor and Strategies, from technical design through launch and ongoing operation\n Build integrations with Coinbase's trading APIs so agent recommendations and user-configured strategies translate into correct, auditable execution\n Develop our agentic harness, including tool calling, orchestration, persistent state, and recovery from failed or partially completed actions\n Shape agent behavior through prompt engineering, evals, and conversation analysis, partnering with our registered investment adviser on changes to financial advice\n Improve service reliability, latency, observability, and execution safety, including retry behavior and safeguards against duplicate actions\n Partner with frontend engineering, product, design, trading infrastructure, and legal/compliance to ship customer-facing capabilities within regulatory guardrails\n \n Required Skills and Experience: \n \n 5+ years of professional software engineering experience, with deep backend expertise and a track record of shipping and operating production services\n Strong experience with API design, distributed systems, data modeling, testing, and debugging production failures\n Proficiency in Go or demonstrated ability to learn it quickly\n Experience building production LLM or agentic systems, including tool calling, orchestration, or evaluation\n Proven ability to take ambiguous projects from zero to production with minimal oversight and sound product and technical judgment\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $186,065 — $218,900 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":186065,"salary_max":218900,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["api-design","llm","distributed-systems","agents","generative-ai","backend","fullstack"],"apply_url":"https://www.coinbase.com/careers/positions/8174232?gh_jid=8174232","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T23:50:37Z","expires_at":"2026-11-13T16:58:01.532962Z","created_at":"2026-10-14T15:21:41.455481Z","updated_at":"2026-10-14T16:58:01.535851Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/add4fc69-019a-44ed-84cb-02a73f033485"},{"id":"91788e64-435a-4da4-adc2-73888874d8f3","company_id":"3da82454-107f-427f-88e7-01f315ef93fb","title":"Senior Technical Partnerships Manager","slug":"senior-technical-partnerships-manager-ad5320e1","description":"OWN YOUR INTELLIGENCE\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nYOUR ROLE\n\nNo one builds the AI infrastructure stack alone. The GPU makers, cloud and datacenter providers, model labs, and enterprise platforms we work with are core to how we reach customers and how we ship. The partnerships that matter in this industry are not logos on a slide — they are shipped integrations, field teams that can actually sell and support a joint solution, and customers who win because both companies showed up together. Very few people know how to make those partnerships real at the technical and commercial level simultaneously.\n\nYou will own our most strategic technical alliances end to end: NVIDIA, hyperscalers, neoclouds, datacenter operators, and the next wave of partners across models, tooling, and enterprise. You will be the person a partner's engineering, product, and field teams trust to turn a signed MOU into something that moves pipeline and ships product.\n\nThe work sits at the intersection of technical depth and commercial execution. You will go deep enough on GPUs, networking, distributed training, and inference stacks to hold your own with partner engineers, and broad enough to run joint go-to-market, executive relationships, and a scalable partner program. You will scope proofs of concept with joint customers, build the enablement that lets partner sellers position us, secure marketplace and co-sell motions, and bring partner roadmaps back into our product and research decisions.\n\nThe partnerships you build will directly shape how Prime Intellect reaches the labs, enterprises, and research teams building on our stack — and how fast we can deliver compute, training, and environments to them.\n\n\n\n\nRESPONSIBILITIES\n\nPartner Relationship Management\n\n - Own 3–5 tier-1 technical partnerships (e.g., NVIDIA, hyperscalers, neoclouds, datacenter operators) as the single accountable lead\n\n - Build relationships across the partner org at every level: alliance managers, developer relations, product and engineering, field sales, and executives\n\n - Run quarterly business reviews and set joint annual plans with clear goals, owners, and metrics\n\n - Navigate partner programs (e.g., NVIDIA Inception, NPN, cloud marketplace and co-sell programs) to unlock credits, benefits, tiering, and visibility\n\n - Negotiate and manage partnership agreements, MOUs, and joint commitments with Legal and Finance\n\nJoint Customer Engagement\n\n - Lead and join joint customer calls with partner account teams, from discovery through technical deep dives and close\n\n - Act as the technical bridge in deals: map customer workloads to the joint solution, scope proofs of concept, and remove blockers\n\n - Coordinate escalations across both companies when joint customers hit issues\n\n - Build a pipeline of partner-sourced and partner-influenced opportunities, and report on it\n\nTechnical Integration \u0026 Product Feedback\n\n - Drive joint technical work: integrations, benchmarks, validated configurations, certifications, and optimizations on partner hardware and software\n\n - Get early access to partner roadmaps, hardware, and SDKs, and translate them into product opportunities for us\n\n - Bring partner and customer feedback into our product and research roadmaps, and advocate for our needs in the partner's roadmap\n\n - Write or co-author reference architectures, technical blog posts, and solution briefs\n\nTraining \u0026 Enablement\n\n - Build enablement content for partner field teams: pitch decks, battlecards, demo scripts, reference architectur","salary_min":250000,"salary_max":300000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","gpu","distributed-systems","agents","llm"],"apply_url":"https://jobs.ashbyhq.com/PrimeIntellect/3e11ec2c-34c1-45c8-a732-ab3001225f25/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T18:46:20.266Z","expires_at":"2026-11-13T16:58:27.616917Z","created_at":"2026-10-14T15:22:05.997825Z","updated_at":"2026-10-14T16:58:27.619663Z","company_name":"Prime Intellect","company_slug":"PrimeIntellect","company_logo_url":"https://www.google.com/s2/favicons?domain=primeintellect.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/91788e64-435a-4da4-adc2-73888874d8f3"},{"id":"8f18ce3b-de45-44c2-bcb4-bc1c243cc19a","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior AI Infrastructure Engineer, Physical Infrastructure","slug":"senior-ai-infrastructure-engineer-physical-infrastructure-ca6b4797","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 CorpTech Infrastructure Engineering builds and operates the foundational infrastructure that powers Anduril at large. We give engineers, researchers, and product teams across the company a place to deploy fast, scalable infrastructure without having to become infrastructure experts themselves. As Anduril's AI and autonomy ambitions grow, our team is responsible for delivering the next generation of compute, networking, and storage capabilities that make cutting edge model training and inference possible company wide.\n ABOUT THE JOB\n We’re looking for a Senior AI Infrastructure Engineer to lead the vision, execution, and long-term stability of how Anduril trains with GPUs at scale. In this role, you will take absolute ownership of cluster robustness, ensuring our high-performance GPU systems are highly available, fault-tolerant, and resilient for ML platform and research teams company-wide. This is a highly hands-on role where your primary focus is logical stability and automated resilience—building self-healing mechanisms to proactively detect and isolate hardware faults, tuning NCCL and high-speed networking, and optimizing Kubernetes, Run:AI, and Ray scheduling. By replacing manual triage with automated deployment tooling and deep observability, you will ensure our massive-scale training infrastructure runs seamlessly and scales without linear headcount growth.\n WHAT YOU'LL DO\n \n Rack, stack, cable, and bring up GPU compute (H200/B200/B300, NVL72) including physical topology, power, cooling, firmware/BIOS, and burn in validation.\n Build and tune the interconnect fabric (NVLink, InfiniBand, RoCE, Spectrum-X) connecting hundreds of GPUs into low latency training and inference clusters.\n Integrate high performance parallel storage (VAST, DDN, Weka) to sustain the throughput demanded by distributed training and terabyte scale multi modal datasets across Anduril's programs.\n Automate cluster deployment and configuration end to end, including infrastructure as code for bring up, firmware/driver management, and fabric config, so new capacity comes online with minimal manual work.\n Operate and extend our Kubernetes/Run:AI environment for GPU scheduling, quota management, and multi tenant workload isolation across research and engineering teams company wide.\n Own fleet health: monitoring, alerting, and rapid triage of hardware and network faults (bad transceivers, GPU Xid errors, NCCL/collective failures, RoCE congestion).\n Onboard engineers and researchers onto the platform and act as their escalation point, working directly alongside them to debug, train, and optimize their workloads whenever infrastructure, not the model, is the bottleneck.\n Partner with product facing teams across Anduril to understand emerging compute needs and translate them into platform capability.\n \n REQUIRED QUALIFICATIONS\n \n 10+ years in a hands on infrastructure, HPC, or datacenter engineering role supporting GPU compute at scale.\n Hands on experience with H200/B200/B300 (or comparable) GPU systems: bring up, cabling, firmware/driver management.\n Experience with high performance interconnects (NVLink, InfiniBand, RoCE, Spectrum-X) in clusters of hundreds of GPUs.\n Experience with high performance parallel storage (VAST, DDN, Weka, Lustre, or similar).\n Kubernetes required; Run:ai or similar GPU scheduling/orchestration experience strongly preferred.\n Strong automation background. You build repeatable, automated deployment pipelines rather than manual processes.\n Able to lift/move 50+ lbs and perform physical datacenter work (rack/stack/cable/troubleshoot).\n Eligible to obtain and maintain an active U.S. Top Secret clearance.\n \n PREFERRED QUALIFICATIONS\n \n Experience with NVIDIA NVL72 rack scale systems.\n Experience supporting LLM token serving/inference infrastructure alongside training clusters.\n Network fabric tuning experience (congestion control, adaptive routing, QoS) for RoCE/InfiniBand at scale.\n Familiarity with GPU/network observability tooling (DCGM, fabric telemetry) and automated fault detection.\n Experience supporting infrastructure as a shared platform serving multiple internal customer teams with differing requirements.\n US Salary Range\n $166,000 — $220,000 USD \n The salary range for ","salary_min":166000,"salary_max":220000,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","payments","cloud","llm","computer-vision","infrastructure"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5261398007?gh_jid=5261398007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T17:17:31Z","expires_at":"2026-11-13T16:57:16.163037Z","created_at":"2026-10-14T15:21:01.333522Z","updated_at":"2026-10-14T16:57:16.165847Z","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/8f18ce3b-de45-44c2-bcb4-bc1c243cc19a"},{"id":"adb9ec1c-9b8c-4e90-bd57-8b6787035ee7","company_id":"76c63eb7-c307-4322-8c2b-c20216feec49","title":"Senior Software Engineer, Data Ingestion","slug":"senior-software-engineer-data-ingestion-ef3cb16f","description":"GET TO KNOW US\n\nHorizon3 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\n \n \n\n\nWHAT YOU'LL DO\n\nThe Sr. Software Engineer on the Data Ingestion team builds and maintains the pipelines that transform raw pentest output into structured, queryable data across the NodeZero platform. NodeZero runs thousands of autonomous pentests — your pipelines are the first link in the chain between execution engine results and the insights customers see. You'll work on high-throughput ETL systems that normalize heterogeneous scan data, push structured findings to graph and relational stores, and feed downstream systems including Asset Inventory, reporting, and analytics.\n\nThis role reports to the Data Ingestion Engineering Manager and works alongside a small team of backend engineers including one P5 technical anchor.\n\n\n\n\nRESPONSIBILITIES\n\n - Design, implement, and operate data ingestion pipelines that process pentest results at scale — scan output, discovered assets, vulnerability findings, and network topology data\n\n - Own end-to-end delivery of pipeline features: schema design, implementation, testing, deployment, and monitoring\n\n - Build and maintain ETL components in Go and/or Python that normalize heterogeneous inputs from NodeZero's execution engines\n\n - Partner with the Asset Inventory and Data Platform teams to define and evolve the data contracts that connect ingestion to downstream consumers\n\n - Diagnose and resolve production issues in pipeline latency, data correctness, and throughput\n\n - Contribute to code and design reviews; provide engineering guidance to P3 engineers on the team\n\n \n\n\nWHAT YOU'LL BRING\n\n\nBACKEND ENGINEERING\n\n - 5+ years of professional software engineering experience with production backend systems\n\n - Strong Go and/or Python proficiency — this team's primary languages\n\n - Demonstrated experience building and operating data pipelines or ETL systems in production (streaming or batch)\n\n - Working knowledge of message queues or event streaming systems (Kafka, RabbitMQ, or equivalent)\n\n\nDATA \u0026 STORAGE\n\n - Experience with relational databases (PostgreSQL or equivalent) — schema design, query optimization, migrations\n\n - Familiarity with graph databases or graph data models is a strong asset\n\n - Understanding of data normalization trade-offs, schema evolution, and backward compatibility\n\n\nPLATFORM \u0026 OPERATIONS\n\n - Experience running services on Kubernetes and containerized environments (Docker)\n\n - Comfort deploying and debugging distributed systems in AWS or equivalent cloud\n\n - Operational mindset: you instrument your code, write runbooks, and own your services through their full lifecycle\n\n\nCOLLABORATION\n\n - Ability to work across team boundaries: you define data contracts with downstream consumers, not just ship to a queue and walk away\n\n - Clear written communication — design docs, PR descriptions, and async updates to distributed teammates\n\n \n\n\nNICE TO HAVES\n\n - Experience in cybersecurity, security tooling, or working with vulnerability or threat data\n\n - Exposure to graph databases (Neo4j, DGraph, or equivalent)\n\n - Experience with Apache Kafka or similar event streaming platforms at production scale\n\n - Background in offensive security tools or pentest workflows — you'll understand the data you're ingesting\n\n \n\n\nTRAVEL REQUIRED\n\nWe are a fully remote company, and this job may require up to 5% of travel to be successful.\n\n \n\n\nCOMPENSATION AND VALUES\n\nAt Horizon3, we believe that our people are our greatest asset, and our compensation philosophy reflects this core value. We are committed to fostering an environment where all employees feel valued, respected, and rewarded for their contributions. Our compensation structure is designed to be fair, competitive, and transparent, ensuring that every team member is recognized and compensated equitab","salary_min":199750,"salary_max":260000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","data-pipeline","security","distributed-systems"],"apply_url":"https://jobs.ashbyhq.com/horizon3ai/8537f395-034a-4a07-8b8a-4925c337f40c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T16:28:51.788Z","expires_at":"2026-11-13T16:56:49.935459Z","created_at":"2026-10-14T15:20:34.950145Z","updated_at":"2026-10-14T16:56:49.938515Z","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/adb9ec1c-9b8c-4e90-bd57-8b6787035ee7"},{"id":"70e145b8-5b41-4b48-a424-a088b204b2a6","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"[2027] Senior Machine Learning Engineer - PhD Early Career","slug":"2027-senior-machine-learning-engineer-phd-early-career-b6d69cf2","description":"Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.  \n At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.  \n A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. \n At Roblox, we believe advanced research belongs in production, driving core algorithmic advances at a global scale. In this role, you’ll own high-impact projects end-to-end, from initial ideation to production deployment and academic publication, while solving complex, high-dimensional challenges at world-scale concurrency. \n Your expertise, across research areas including Computer Vision and Graphics, multimodality, NLP, or recommendation systems, will directly shape the experience for millions of daily active users. Come build the AI-driven infrastructure powering the future of immersive entertainment.\n You Will \n \n Prototype and implement advanced AI and machine learning solutions that drive core platform features and innovation at scale.\n Develop and deploy cutting-edge models (e.g., deep learning, generative AI, multimodal architectures) to solve complex, high-impact technical challenges.\n Collaborate with applied researchers, engineers, and product teams to translate advanced research concepts into production-ready systems.\n Translate complex research into scalable, robust infrastructure that directly impacts hundreds of millions of daily active users.\n Work backward from user and product needs to architecture, and deliver ML solutions that improve platform engagement, safety, and content ecosystem growth.\n \n You Have \n \n Possess or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.\n Deep expertise and curiosity in a relevant technical domain, such as deep learning, computer vision, NLP, reinforcement learning, or distributed systems.\n Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.\n A strong research track record, evidenced by multiple publications and presentations in rigorous peer-reviewed venues.\n \n You may redact age, date of birth, and dates of attendance/graduation from your resume.\n As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.\n For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page .\n Annual Salary Range\n $196,750 — $243,290 USD \n Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).\n Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.\n For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.","salary_min":196750,"salary_max":243290,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["computer-vision","deep-learning","distributed-systems","generative-ai","nlp","reinforcement-learning","machine-learning"],"apply_url":"https://careers.roblox.com/jobs/8242623?gh_jid=8242623","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T16:05:13Z","expires_at":"2026-11-13T17:02:53.108743Z","created_at":"2026-10-14T15:24:56.108637Z","updated_at":"2026-10-14T17:02:53.113421Z","company_name":"Roblox","company_slug":"roblox","company_logo_url":"https://www.google.com/s2/favicons?domain=roblox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/70e145b8-5b41-4b48-a424-a088b204b2a6"},{"id":"4290888b-e1c9-49a5-9d2a-4ba08900207b","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Machine Learning Engineer, Content Visual AI","slug":"staff-machine-learning-engineer-content-visual-ai-1a89c7fb","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n The User and Content Foundations org is responsible for deeply understanding our content, users and their interactions by generating high-quality, reusable signals and insights that power relevance and personalization across the platform. We work at the intersection of distributed machine learning, large multimodal models, data infrastructure, and product adoption to build foundational capabilities that support our partners, including Discovery, Search, Growth, and Ads. We are looking for an experienced Staff Machine Learning Engineer / Technical Lead who can drive the team’s technical direction, lead the team in building scalable content understanding systems, and make an impact on core Pinterest user and business outcomes.  In this role, you will lead ambiguous, high-impact scientific and engineering efforts that create reusable representations, models, and signals.  You’ll work across research, machine learning, infrastructure, and engineering domains to turn advances in VLMs, LLMs, multimodal learning and sequence modeling into impact.  This role is ideal for a deeply technical leader who combines strong ML judgment with product intuition. Expertise in visual representation learning and content understanding is especially valuable; experience with user understanding, recommender systems and LLMs is also highly relevant.\n What will you be doing: \n \n Set the technical direction and multi-quarter strategy for foundational ML capabilities across visual representation learning, multimodal content understanding, and LLM-based personalization.\n Lead high-impact scientific and technical initiatives from problem definition and research strategy through experimentation, productionization, and adoption.\n Build reusable embeddings, representations, semantic signals, and ML infrastructure while advancing techniques such as VLMs, LLMs, sequence modeling, self-supervised learning, retrieval, and distillation.\n Partner with Product, Data Science, Applied Science, and Engineering to translate foundational capabilities into product outcomes and influence cross-functional roadmaps and investments.\n Establish rigorous practices for modeling, data pipelines, distributed training, inference, evaluation, experimentation, and operational excellence while mentoring engineers and scientists.\n \n What we’re looking for: \n \n Minimum 7 years of industry experience, including 2+ years of tech leading teams\n MS or PhD degree in computer science, machine learning, or equivalent industry experience.\n Publications at top machine learning, multimodal and/or data mining conferences (e.g., NeurIPS, ICML, CVPR, ECCV, ACL, KDD, SIGIR, etc.) or open-source ML experience\n Hands-on experience with large-scale distributed training of generative models (LLMs, VLMs, sequence models).\n Hands-on experience with distributed tooling for ML data pipelines (e.g. Spark, Hive, MapReduce)\n Hands-on experience leading ambiguous ML and research efforts in building, applying and improving GenAI models for content understanding, search and recommendation systems.\n Technical leadership and experience in setting direction for roadmaps that span modeling, data pipelines and productionization, and aligning stakeholders on priorities, trade-offs, and execution plans.\n Excellent cross-functional communication and collaboration skills\n \n Relocation Statement: \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n In-Office Requirement Statement: \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\n This role will need to be in the office for in-person collaboration 1-2 times/quarter and can be situated anywhere in the U","salary_min":189308,"salary_max":389753,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","distributed-systems","llm","generative-ai","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8247246","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T15:49:26Z","expires_at":"2026-11-13T16:57:51.232293Z","created_at":"2026-10-14T15:21:31.463492Z","updated_at":"2026-10-14T16:57:51.235425Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4290888b-e1c9-49a5-9d2a-4ba08900207b"},{"id":"89d58d57-03e8-4684-83b2-3121d619b65f","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Software Engineer, ML Serving Platform","slug":"software-engineer-ml-serving-platform-c430ad40","description":"About the Team \n DoorDash’s ML Serving Platform delivers tens of millions of predictions per second , powering search, recommendations, advertising, delivery estimates, and logistics across DoorDash, Wolt, and Deliveroo.\n Our customers are modelers and engineering teams across our internal business verticals. We build self-serve infrastructure that empowers them to bring new models into production, adopt open source software and models, and expand what they can accomplish with machine learning at scale.\n We work at the intersection of a rapidly evolving open source ecosystem and demanding production workloads. With active customer demand and growing modeling ambitions, we’re advancing the infrastructure behind today’s predictions while building the capabilities that enable the next generation of ML innovation.\n About the Role \n You’ll help build the next generation of our ML serving platform, connecting request routing and online feature retrieval with model inference on CPU and GPU infrastructure. You’ll tackle challenging infrastructure problems involving latency, reliability, resource efficiency, and scale, and make those capabilities accessible through self-serve tools and workflows.\n Working alongside experienced platform engineers, you’ll own defined projects from technical design and implementation through testing, rollout, and production support. You’ll partner directly with internal teams to understand emerging modeling requirements, remove adoption barriers, and turn advances in open source technology into measurable production improvements.\n You’re excited about this opportunity because you will… \n \n Empower modelers through self-serve infrastructure. Build tools, APIs, and workflows that help internal teams deploy, configure, validate, and operate models independently, accelerating ML adoption across business verticals.\n Bring open source innovation into production. Evaluate and integrate evolving inference frameworks and enable open source models, translating promising capabilities into reliable, efficient services at scale.\n Solve demanding inference infrastructure problems. Improve the systems that route prediction requests, retrieve online features, and execute models on a platform serving tens of millions of predictions per second.\n Help evolve our disaggregated serving architecture. Build modular components that allow routing, feature retrieval, and model execution to evolve and scale independently as workloads and modeling requirements change.\n Improve Kubernetes deployment and autoscaling. Help workloads respond to changing traffic while meeting latency and availability requirements and using CPU and GPU resources efficiently.\n Make adoption and rollout easier. Build integrations, validation, and migration tooling that help teams adopt new serving capabilities and our unified global platform with confidence.\n Own performance and reliability in production. Use benchmarking, profiling, metrics, and tracing to identify bottlenecks; participate in on-call and improve automation and runbooks to make the platform easier to operate.\n \n We’re excited about you because… \n \n You have 2+ years of software engineering experience building and maintaining production services or infrastructure.\n You have strong computer science fundamentals and proficiency in a backend or systems programming language such as Java, Kotlin, Go, C++, or Python.\n You understand distributed systems fundamentals, including concurrency, networking, timeouts, failure handling, and performance trade-offs.\n You enjoy challenging infrastructure problems and can independently turn a defined problem into a technical design, tested implementation, and safe production rollout.\n You have experience debugging production systems and using operational data to improve reliability, performance, or cost.\n You care about the engineers using your platform and collaborate effectively with customers and partners to make complex infrastructure easier to adopt.\n You hold a degree in Computer Science or a related field, or have equivalent practical experience.\n \n Nice to Have \n \n Experience with ML inference infrastructure, online feature retrieval, or other latency-sensitive distributed services.\n Experience operating containerized workloads on Kubernetes, including deployment, resource management, or autoscaling.\n Experience building self-serve developer platforms, APIs, or automation that helps other engineers move faster.\n Experience integrating open source infrastructure or models and validating their behavior under production workloads.\n Familiarity with CPU/GPU performance profiling, inference runtimes, or model deployment workflows.\n \n Applications for this position are accepted on an ongoing basis\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 lo","salary_min":130600,"salary_max":192000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["mlops","distributed-systems","fine-tuning","cloud","gpu","healthcare","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8263726","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T14:17:36Z","expires_at":"2026-11-13T17:03:28.772861Z","created_at":"2026-10-14T15:25:31.414102Z","updated_at":"2026-10-14T17:03:28.775658Z","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/89d58d57-03e8-4684-83b2-3121d619b65f"},{"id":"d6ccab06-8408-4826-b3a1-259ba586f060","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Software Engineer, Machine Learning Platform - MDX","slug":"software-engineer-machine-learning-platform-mdx-445b9a46","description":"About the Team \n Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented engineers to help us create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.\n About the Role \n At DoorDash, our Data Scientists and ML Engineers have the opportunity to dive into a wealth of delivery data to improve company-wide ML workflows such as Search \u0026 Recommendations, Dasher Assignment, ETA Prediction, and Dasher Capacity Planning. You will join a small team to build systems that empower efficient machine learning at scale. This is a hybrid opportunity in San Francisco, Sunnyvale or Seattle.\n You’re excited about this opportunity because you will…\n \n Build a world-class ML platform where models are developed, trained, and deployed seamlessly\n Work closely with Data Scientists and Product Engineers to evolve the ML platform as per their use cases \n You will help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches\n You will work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day\n You will help design and drive directions for the centralized machine learning platform that powers all of DoorDash's business.\n Improve the reliability, scalability, and observability of our training and inference infrastructure.\n \n We’re excited about you because… \n \n B.S., M.S., or PhD. in Computer Science or equivalent\n Exceptionally strong knowledge of CS fundamental concepts and OOP languages\n 2+ years of industry experience in software engineering\n Prior experience building machine learning systems in production such as enabling data analytics at scale\n Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts\n Systems Engineering - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems\n \n Nice To Haves \n \n Experience with challenges in real-time computing\n Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure\n Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow\n Familiar with Spark, MLLib, Databricks,MLFlow, Apache Airflow, Dagster and similar related technologies.\n Familiar with large language models like GPT, LLAMA, BERT, or Transformer-based architectures\n Familiar with a cloud based environment such as AWS\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 $130,600 — $192,000 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 fo","salary_min":130600,"salary_max":192000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["healthcare","pytorch","cloud","llm","deep-learning","distributed-systems","fine-tuning","tensorflow"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8264534","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T14:17:34Z","expires_at":"2026-11-13T17:03:28.767496Z","created_at":"2026-10-14T15:25:31.409011Z","updated_at":"2026-10-14T17:03:28.770438Z","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/d6ccab06-8408-4826-b3a1-259ba586f060"},{"id":"64d23aa4-9ec2-400e-a028-2a5364b6e205","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Software Engineer, Machine Learning Platform - Gen AI","slug":"software-engineer-machine-learning-platform-gen-ai-ba861ebf","description":"About the Team \n DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.\n About the Role \n You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll work across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability. This role is ideal for an engineer who enjoys pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly.\n You’re excited about this opportunity because you will… \n \n Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company.\n Work on our open-weights serving stack — real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.\n Design scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases\n Push the cost and latency frontier of GPU inference — turning batch jobs that took days into hours and cutting inference cost by multiples — while giving product teams a clean choice across open-weight and closed-source models with reliability, fallback, observability, and cost controls built in.\n Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence.\n Partner closely with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives.\n Shape the future of DoorDash’s centralized GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimization, and other post-training and agentic techniques — enabling the next generation of AI-powered products, agents, automation, and personalization.\n \n We’re excited about you because… \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 engineering fundamentals, especially in Python and distributed systems.\n Experience building production services, APIs, data pipelines, or ML infrastructure at scale.\n Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization.\n Hands-on experience with LLM inference and/or fine-tuning of open-weight models in production — serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine-tuning (SFT/DPO/LoRA).\n Ability to work across ambiguous, fast-moving technical areas and turn customer use cases into reusable platform capabilities\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 \n Nice To Haves \n \n Experience with LLM inference engines and serving frameworks (e.g., vLLM, SGLang, TensorRT-LLM) in production\n Experience with distributed/multi-node fine-tuning and training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluation\n GPU performance work — multi-node/distributed inference, KV-cache/memory optimization, quantization (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuning\n Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless/elastic GPU platforms (e.g., Modal), or high-throughput batch systems\n Experience with LLM gateways, model routing, vendor abstraction, or cost attribution\n Experience building developer platforms, internal platforms, or self-serve infrastructure\n Experience building and deploying AI a","salary_min":130600,"salary_max":192000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["generative-ai","cloud","embeddings","mlops","fine-tuning","llm","distributed-systems","agents"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8264542","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T14:17:32Z","expires_at":"2026-11-13T17:03:28.762428Z","created_at":"2026-10-14T15:25:31.403168Z","updated_at":"2026-10-14T17:03:28.76533Z","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/64d23aa4-9ec2-400e-a028-2a5364b6e205"},{"id":"84267438-bcb6-4a44-97ac-4f18bdb2ad77","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Research Systems Engineering","slug":"staff-software-engineer-research-systems-engineering-27aecffe","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models. Every other team at Anthropic depends on these systems.\n In this role, you'll work directly with our Research teams to build the reliable, scalable, performant infrastructure our research depends on. This is a cross-functional systems team: you'll scope and lead complex, multi-month infrastructure projects and resolve the performance and scalability bottlenecks that limit how fast we can grow.\n Key responsibilities\n \n Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system\n Build deep partnerships with researchers and Research teams to understand their needs and deliver for them\n Mentor other engineers and help raise the technical bar for the team\n Build alignment on technical direction across multiple teams, working through ambiguous problem spaces\n Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow\n Lead the improvement of operational processes across Infrastructure, such as incident response, postmortems, and on-call rotations, so the team learns from every incident\n \n Minimum qualifications\n \n Experience designing, building, and operating large-scale distributed systems or infrastructure in production\n Experience independently scoping and delivering complex, ambiguous, multi-month technical projects\n Prior experience as a technical lead or mentor for other engineers\n Experience making architectural decisions that other engineers and teams build on top of\n Strong software engineering fundamentals and proficiency in at least one programming language (e.g., Python, Rust, Go, Java)\n Experience with modern cloud infrastructure (e.g., Kubernetes, infrastructure as code, AWS, GCP)\n Strong written and verbal communication skills, with experience building alignment across multiple teams or stakeholders\n \n Preferred qualifications\n \n 10+ years of software engineering experience, not including internships\n Experience with machine learning infrastructure (e.g., GPUs, TPUs, Trainium) and associated networking infrastructure (e.g., NCCL)\n Low-level systems experience (e.g., Linux kernel tuning, eBPF)\n Experience applying security or privacy engineering best practices\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're eve","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","alignment","cloud","research","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5447118008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T20:26:11Z","expires_at":"2026-11-13T16:54:56.973202Z","created_at":"2026-10-14T15:17:23.460298Z","updated_at":"2026-10-14T16:54:56.975982Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/84267438-bcb6-4a44-97ac-4f18bdb2ad77"},{"id":"e9149594-5872-43b7-bba2-b0bd2a94c556","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Mission Software Engineer, Mission Systems, Networking","slug":"mission-software-engineer-mission-systems-networking-c4b6b336","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 Air Dominance \u0026 Strike (AD\u0026S) is responsible for autonomous robotics systems like the Fury unmanned fighter jet and the Barracuda family of advanced effects. The AD\u0026S Mission Systems Software team builds the distributed infrastructure that connects these vehicles to command and control. We develop the messaging, orchestration, and networking backbone that ties individual vehicles into coordinated, multi-vehicle operations. Our engineers develop the services that integrate with Lattice OS, coordinate fleets of vehicles in the field, and task and manage mission payloads and effects. We are looking for engineers excited to own from cradle-to-grave resilient, distributed mission software that supports the full range of AD\u0026S initiatives: from early concept simulation to live operations and large scale fleet management.\n REQUIRED QUALIFICATIONS \n \n \n BS, MS, or PhD in Computer Science, Software Engineering, Mathematics, Physics, or related field.\n \n Ability to diagnose \u0026 root cause arbitrary \u0026 complex networking or routing failures in multi hop networks\n \n Ability to read packet captures and use standard network debugging tools (tcpdump, Wireshark, etc.)\n \n Experience with end to end testing of both unicast and multicast data flows\n \n Strong understanding of networking fundamentals: TCP/UDP, socket programming, MTU, multicast, TLS/mTLS\n \n Experience utilizing timing protocols such as NTP and PTP\n \n CCNA or equivalent exp.\n \n A high comfort working in a Linux environment\n \n Experience with systemd \n \n Familiarity with Kubernetes and container orchestration\n \n Experience with Git \u0026 GitHub\n \n 2-3+ years of experience using C++, Rust, or equivalent mid-level language\n \n Travel up to 30% of time to build, test, and deploy capabilities in the real world\n Eligible to obtain and maintain an active U.S. Secret security clearance\n \n Track record of high ownership and bias for action\n \n PREFERRED QUALIFICATIONS \n \n \n Experience building or maintaining distributed systems (message buses, RPC frameworks, consensus protocols, or similar)\n \n Familiarity with asynchronous programming models (async/await, event loops, futures)\n \n Comfort working with Protocol Buffers and/or gRPC\n \n Experience with Linux’s FRR package\n \n Active Secret U.S. security clearance\n \n  \n US Salary Range\n $166,000 — $220,000 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 candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.\n Please always verify communications: \n \n Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.\n Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you su","salary_min":166000,"salary_max":220000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["api-design","payments","robotics","distributed-systems","cloud","computer-vision","gpu"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5260436007?gh_jid=5260436007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T18:48:40Z","expires_at":"2026-11-13T16:57:15.933818Z","created_at":"2026-10-14T15:21:01.07217Z","updated_at":"2026-10-14T16:57:15.936654Z","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/e9149594-5872-43b7-bba2-b0bd2a94c556"}],"page":1,"per_page":20,"total":1536,"total_is_exact":true,"total_pages":77}