{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"8ad2920a-4171-4759-864b-2007360008f4","company_id":"3dacb2af-b4b4-42ae-9b16-4e0203d290e4","title":"Machine Learning Engineering Intern, Summer 2027","slug":"machine-learning-engineering-intern-summer-2027-53172cc3","description":"About Wing:  \n Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us. \n About the Program:  \n Join Wing's 12-week paid summer internship! This is a hybrid, in-person program based in Palo Alto, CA, with start dates in May or June. Eligible candidates must be a current student enrolled in a degree program and intend to return to the program after the completion of the summer internship. \n About the Opportunity: \n Wing is looking for a Machine Learning Engineer Intern to join our Perception team based in Palo Alto, CA. You will be at the forefront of advancing our autonomous drone delivery system, leveraging deep learning to ensure our aircraft navigate the world with precision and safety.  At Wing, you aren’t just building models in a vacuum; you have access to tens of thousands of hours of flight data from a diverse sensor suite\n In this role, you will: \n \n Help us track towards our goal of building unified and/or generalized Perception models that helps Wing aircraft systems gracefully handle a wide variety of edge cases they experience when operating in the real world\n Analyze real-world data, coming up with new ideas on how to improve our existing Perception pipelines with state-of-the-art foundational and end-to-end geometric models\n Gain experience with leveraging large amounts of diverse, real-world data from a fleet of thousands of robots to build ML models that solve real problems.\n Make a measurable impact on Wing's ability to scale our operations more rapidly, at the forefront of the rapidly growing drone delivery industry.\n Be a part of a dynamic and collaborative team.\n \n What You’ll Need:  \n \n Currently pursuing a Master's, or PhD degree in Aerospace Engineering, Mechanical Engineering, Computer Science, Computer Vision, Robotics, Electrical Engineering, or related field, graduating between December 2027 and August 2028\n Strong examples of previous engineering experience from past internships and/or academic or extracurricular projects.\n Strong grasp of basic physics and engineering fundamentals in Computer vision\n Strong grasp of modern computer vision technologies such as self-supervised Vision Transformer foundation model, Vision Language Models, VLAs, and hands-on experience in at-least one of those domains\n Experience with C++ and/or Python.\n The US base salary range for this internship position is the salary range below + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process.\n Salary Range\n $128,000 — $135,000 USD \n Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.\n If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our  Candidate Accommodations Request Form .","salary_min":128000,"salary_max":135000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["robotics","computer-vision","cloud","deep-learning","generative-ai","machine-learning"],"apply_url":"https://wing.com/careers/8872479002?gh_jid=8872479002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T22:00:01Z","expires_at":"2026-11-13T17:02:54.727732Z","created_at":"2026-10-14T15:24:57.757978Z","updated_at":"2026-10-14T17:02:54.730712Z","company_name":"Wing","company_slug":"wing","company_logo_url":"https://www.google.com/s2/favicons?domain=wing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8ad2920a-4171-4759-864b-2007360008f4"},{"id":"2bdabd0b-9451-4388-b502-2ba7d839c43f","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Machine Learning Engineer, Drive","slug":"senior-machine-learning-engineer-drive-202e134e","description":"About the Team\n DoorDash Drive powers deliveries placed through merchants' own channels—including their websites, mobile apps, and phone orders—using DoorDash's logistics network. The Drive Machine Learning team builds the prediction and intelligence systems that power this business, including delivery and pickup time estimation, merchant prep-time prediction, order release optimization, logistics decision-making, and AI-powered delivery quality signals. Drive presents a unique machine learning challenge. Every merchant has different operational workflows, preparation patterns, and customer expectations, requiring models that generalize across millions of deliveries while adapting to highly diverse merchant behavior. Our team has significant opportunities to improve prediction accuracy, optimize logistics decisions, and build AI-native experiences that directly improve merchant, consumer, and dasher outcomes.\n About the Role\n As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration. Your work will span several high-impact problem areas:\n \n Build next-generation machine learning models for delivery ETA, pickup ETA, merchant prep-time estimation, and order release prediction that improve reliability for merchants and consumers.\n Develop deep learning models that leverage large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.\n Apply reinforcement learning and optimization techniques to improve logistics decision-making, assignment strategies, and marketplace efficiency.\n Build AI-native product experiences using large language models (LLMs) and vision-language models (VLMs). For example, transform pickup photos, item verification flows, receipts, and drop-off images into structured quality signals that help verify orders, prevent delivery defects, and improve issue resolution.\n Design and run rigorous online experiments, production monitoring, and model iteration to continuously improve performance.\n Partner closely with software engineers, product managers, data scientists, and platform teams to bring new machine learning capabilities into production at scale.\n You'll have the opportunity to work across traditional machine learning, deep learning, reinforcement learning, optimization, and multimodal AI while solving some of the most challenging logistics problems at DoorDash.\n \n You're excited about this opportunity because... \n \n You enjoy solving large-scale machine learning problems that directly impact millions of deliveries.\n You have a strong sense of ownership and enjoy taking models from research through production.\n You're comfortable working in ambiguous environments where experimentation and iteration drive product decisions.\n You care about both model quality and production reliability.\n You're excited to work across a diverse set of ML techniques—from neural networks and optimization to multimodal AI.\n You collaborate well across engineering, product, and data science teams.\n \n We’re excited about you because… \n \n 5+ years of industry experience building and shipping production machine learning systems with measurable business impact (Bachelor's, Master's, or PhD).\n Strong experience developing production machine learning models using modern deep learning frameworks such as PyTorch and distributed data processing technologies such as Spark and Airflow.\n Experience building, deploying, monitoring, and maintaining production ML systems end-to-end.\n Strong software engineering skills in Python and experience with modern ML infrastructure and tooling.\n Deep expertise in at least one of the following areas:\n \n Deep Learning\n Reinforcement Learning\n Optimization / Operations Research\n Large Language Models (LLMs) or Vision-Language Models (VLMs)\n \n Experience applying machine learning to estimation, ranking, prediction, optimization, or decision-making problems at production scale.\n Hands-on experience with LLMs or VLMs is a strong plus.\n Experience in logistics, marketplaces, or delivery platforms is helpful but not required.\n Proficiency using AI-assisted development tools (e.g. Claude Code, Codex, Cursor) throughout the software development lifecycle.\n You are located or are planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA.\n Compensation \n The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.  Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about yo","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","deep-learning","reinforcement-learning","cloud","llm","generative-ai","healthcare","pytorch"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8221807","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:42:26Z","expires_at":"2026-11-13T17:03:28.706911Z","created_at":"2026-10-14T15:25:31.350903Z","updated_at":"2026-10-14T17:03:28.710264Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2bdabd0b-9451-4388-b502-2ba7d839c43f"},{"id":"501a4fae-853d-480b-9dbb-39daa44f8047","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Machine Learning Engineer, Fulfillment Planning","slug":"staff-machine-learning-engineer-fulfillment-planning-53570b60","description":"About the Team \n The Fulfillment Planning team builds the intelligence that powers DoorDash’s logistics network. We optimize how deliveries are planned and executed across the full delivery lifecycle, improving customer experience, merchant outcomes, Dasher efficiency, and DoorDash profitability.  Our mission is to improve fulfillment quality while reducing fulfillment cost. We do this by applying machine learning, optimization, and systems engineering to the core decisions behind assignment, routing, batching, timing, and fulfillment estimation.\n The team works on some of DoorDash’s most important logistics systems, including:\n \n The core assignment engine that matches deliveries with Dashers in real time.\n Real-time ETA and fulfillment estimation systems for consumers, Dashers, and merchants across diverse geographies and all business lines.\n Assignment and planning algorithms for specialized delivery types, including grocery, retail, parcel, and catering.\n ML models and optimization algorithms that shape demand, improve service quality, and reduce cost.\n Tier-0 logistics services that require high reliability, low latency, and strong operational discipline.\n \n The team also builds reusable ML systems and modeling patterns that scale across DoorDash’s logistics ecosystem. This role will help define the technical direction and best practices for logistics ML at DoorDash.\n About the Role \n We’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of large-scale production ML systems that drive real-time decisioning across DoorDash’s fulfillment ecosystem.\n You will start by owning ML systems for assignment and fulfillment estimation, partnering closely with Product, Data Science, Engineering, and Platform teams to improve delivery quality, cost, and efficiency. Over time, you may also contribute to adjacent areas such as batching, fulfillment execution, demand shaping, and logistics optimization across DoorDash’s business lines.\n This is a high-impact individual contributor role for someone who enjoys building 0→1 ML systems, operating at Staff-level scope, and influencing technical direction across multiple teams. You will define architectures, set modeling and deployment standards, mentor other engineers, and help shape how DoorDash applies machine learning to logistics at scale.\n You’re excited about this opportunity because you will… \n \n Own and build foundational ML systems that directly impact delivery quality, cost, and overall logistics efficiency across DoorDash.\n Work on challenging, real-world machine learning problems , including real-time assignment, routing, and fulfillment estimation.\n Lead 0→1 ML initiatives , defining how machine learning and optimization are applied across fulfillment products.\n Influence architecture, strategy, and execution for a Tier-0 service critical to DoorDash’s logistics platform.\n Collaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.\n Establish best practices for model development, deployment, monitoring, retraining, and governance.\n Define and lead DoorDash’s cutting-edge AI vision for logistics: an LLM-inspired foundation model for intelligence across logistics\n Mentor other engineers and raise the technical bar for logistics ML across the organization.\n \n We’re excited about you because… \n \n You have 8+ years of industry experience building and deploying production-scale machine learning systems.\n You have strong machine learning fundamentals and know how to apply them to large-scale production systems.\n You are fluent in Python\n You have hands-on experience with modern ML frameworks, especially deep learning frameworks.\n You have designed, launched, and operated mission-critical ML models or systems in production, including monitoring, retraining, reliability, and governance.\n You can lead complex technical projects end to end and influence stakeholders across multiple teams or organizations.\n You communicate clearly with both technical and non-technical audiences.\n You are comfortable operating in ambiguous problem spaces and turning 0→1 ideas into production systems.\n You have built or shipped large-scale ML models for recommendation, ads, marketplace, logistics, or other domains.\n You have experience with knowledge distillation from large teacher models into efficient production models.\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares ","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","healthcare","cloud","generative-ai","llm","deep-learning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8224336","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:30:37Z","expires_at":"2026-11-13T17:03:28.79242Z","created_at":"2026-10-14T15:25:31.434336Z","updated_at":"2026-10-14T17:03:28.795093Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/501a4fae-853d-480b-9dbb-39daa44f8047"},{"id":"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":"30f0bfd5-b030-48f6-9124-0c1234f28ba7","company_id":"31ae48bc-c938-4c26-a348-0bf3c089a446","title":"Staff Product Manager, AI Inference","slug":"staff-product-manager-ai-inference-85275e80","description":"CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at  www.coreweave.com . \n About the Team \n As the Staff Product Manager - AI Inference, you will lead CoreWeave's strategic efforts in shaping and developing cutting-edge AI inference services that drive innovation and business outcomes for our customers. You will collaborate closely with engineers, designers, and industry partners to create world-class products that empower organizations to build, deploy, scale, and optimize AI models and applications efficiently and effectively.\n The ideal candidate is passionate about AI and cloud technologies, with a deep understanding of the foundation model architectures, AI inference landscape, AI application ecosystem, cloud-native technologies, and the competitive landscape. You will leverage market insights and technical expertise to define the product vision, roadmap, and go-to-market strategy, ensuring that CoreWeave builds on its market-segment position as the leading AI Hyperscaler.\n Key Responsibilities: \n \n Product Vision and Strategy: Help refine the product strategy for AI application cloud services aimed at foundational model Inference, along with focus on optimization across the entire CoreWeave product portfolio for AI workloads. Solve novel problems related to scaling AI model inference on specialized hardware.\n Roadmap Development: Own the product roadmap for AI inference services, balancing near-term customer needs with long-term vision, to deliver differentiated and scalable AI cloud services.\n AI and Cloud Expertise: Stay current on advancements in AI/ML technologies including inference engines, model serving architectures, cloud infrastructures, and software development methodologies to inform product decisions and foster innovation.\n Define product portfolio: Manage ambiguity and complexity of a fast evolving AI landscape to define new product investments and develop a portfolio of inference capabilities that deliver long-term differentiation and customer value.\n Customer Engagement: Collaborate with key customers to understand their AI workloads, pain points, and future requirements to continuously improve our service offerings.\n Cross-functional Leadership: Collaborate with engineering, sales, marketing, and customer success teams to ensure seamless product development and deployment.\n Market Analysis: Analyze market trends, customer feedback, and the competitive landscape to identify growth opportunities and ensure CoreWeave stays ahead of industry trends.\n Go-to-Market Strategy: Partner with industry partners, marketing, and sales teams to develop and execute effective go-to-market strategies for AI cloud services, including pricing strategies, positioning, messaging, and competitive differentiation.\n \n Qualifications: \n \n Experience: 8+ years of experience in product management, with at least 5 years in the cloud services or AI/ML market segment.\n Technical Knowledge: Hands on practitioner and deep understanding of AI/ML workloads including foundation model inference, inference engines such as vllm, SGLang, TensorRT-llm, and llm-d, inference optimization techniques such as quantization and speculative decoding, cloud infrastructure (GPUs), and cloud-native architectures (Kubernetes, microservices).\n Leadership: Proven ability to lead cross functional teams, with strong decision-making, project management, and mentoring skills.\n Customer-Centric Approach: Demonstrated experience working closely with customers to identify needs and translate them into product features and solutions.\n Communication Skills: Excellent verbal and written communication skills with the ability to influence cross-functional teams and stakeholders.\n Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. MBA or equivalent experience is a plus.\n Visionary Leadership: Ability to think strategically while being able to dive into technical details to guide the product team.\n Results-Oriented: Proven track record of driving business growth through innovative product solutions in the AI and cloud space.\n \n Why CoreWeave? \n At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:\n \n Be Curious at Your Core\n Act Like an Owner\n Empower Employees\n Deliver Best-in","salary_min":207000,"salary_max":275000,"location":"Sunnyvale, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["microservices","mlops","cloud","generative-ai","llm","inference"],"apply_url":"https://coreweave.com/careers/job?4720733006\u0026board=coreweave\u0026gh_jid=4720733006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T14:43:58Z","expires_at":"2026-11-13T16:56:02.427193Z","created_at":"2026-10-14T15:20:12.017713Z","updated_at":"2026-10-14T16:56:02.430397Z","company_name":"CoreWeave","company_slug":"coreweave","company_logo_url":"https://www.google.com/s2/favicons?domain=coreweave.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/30f0bfd5-b030-48f6-9124-0c1234f28ba7"},{"id":"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":"362dd4a4-f865-4d4a-9a7a-bc7e1b3dff50","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Staff Machine Learning and Bioinformatics Scientist (Multi-Cancer Early Detection)","slug":"staff-machine-learning-and-bioinformatics-scientist-multi-cancer-early-detection-df2fad4b","description":"Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients.\n PRIMARY RESPONSIBILITIES: \n \n Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data\n Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group\n Prototype, test and productionize ML models using scalable infrastructure\n Own key technical deliverables within larger projects and help shape the team’s research roadmap\n Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies\n Keep raising the bar through code and design reviews across projects\n Translate complex results into clear stories for technical and non-technical audiences\n Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence\n \n QUALIFICATIONS: \n \n PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD\n Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data\n Proven track record of innovation and technical leadership in complex method development projects\n Expertise in deep learning and multimodal foundation models\n Proficient in Python and its scientific computing ecosystem\n Scientific rigor throughout the R\u0026D process, with eagerness to teach and learn new computational methods and biology\n Excellent communication skills and a collaborative approach across teams\n \n Preferred Experience: \n \n Familiarity with DNA methylation and other epigenomic data\n Experience with cell-free DNA and liquid biopsy samples\n Background in cancer genomics and diagnostics\n Hands-on work with multimodal foundation models applied to biological data\n The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years \u0026 depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.\n Remote USA\n $163,200 — $204,000 USD \n OUR OPPORTUNITY \n Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.\n The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.\n WHAT WE OFFER \n Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!\n For more information, visit www.natera.com .\n Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.\n All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws.\n If you are based in California, we encourage you to read this important information for California residents.  \n Link: https://www.natera.com/notice-of-data-collection-california-residents/ \n Please be","salary_min":163200,"salary_max":204000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","deep-learning","healthcare","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6220885004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T22:10:48Z","expires_at":"2026-11-13T16:58:38.001158Z","created_at":"2026-10-14T15:22:15.63645Z","updated_at":"2026-10-14T16:58:38.003762Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/362dd4a4-f865-4d4a-9a7a-bc7e1b3dff50"},{"id":"51543c6e-0d4b-4d56-b403-d772dc9cc157","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Staff Machine Learning and Bioinformatics Scientist (Multi-Cancer Early Detection)","slug":"staff-machine-learning-and-bioinformatics-scientist-multi-cancer-early-detection-bbaf4d4a","description":"Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients.\n PRIMARY RESPONSIBILITIES: \n \n Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data\n Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group\n Prototype, test and productionize ML models using scalable infrastructure\n Own key technical deliverables within larger projects and help shape the team’s research roadmap\n Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies\n Keep raising the bar through code and design reviews across projects\n Translate complex results into clear stories for technical and non-technical audiences\n Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence\n \n QUALIFICATIONS: \n \n PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD\n Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data\n Proven track record of innovation and technical leadership in complex method development projects\n Expertise in deep learning and multimodal foundation models\n Proficient in Python and its scientific computing ecosystem\n Scientific rigor throughout the R\u0026D process, with eagerness to teach and learn new computational methods and biology\n Excellent communication skills and a collaborative approach across teams\n \n Preferred Experience: \n \n Familiarity with DNA methylation and other epigenomic data\n Experience with cell-free DNA and liquid biopsy samples\n Background in cancer genomics and diagnostics\n Hands-on work with multimodal foundation models applied to biological data\n \n Compensation \u0026 Total Rewards  \n This range reflects a good-faith estimate of the base pay we reasonably expect to offer at the time of  hire. Final compensation will vary based on experience, qualifications, and internal equity considerations. \n This position is also eligible for additional compensation and benefits through Natera’s robust Total Rewards program, including: \n \n \n Annual performance incentive bonus \n \n Long-term equity awards \n \n Comprehensive health benefits (medical, dental, vision) \n \n 401(k) with company match \n \n Generous paid time off and company holidays \n \n Additional wellness and work-life benefits \n \n \n Compensation Range \n $169,800 — $212,300 USD \n OUR OPPORTUNITY \n Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.\n The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.\n WHAT WE OFFER \n Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!\n For more information, visit www.natera.com .\n Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.\n All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability","salary_min":169800,"salary_max":212300,"location":"San Carlos, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","deep-learning","healthcare","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6221940004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T22:10:46Z","expires_at":"2026-11-13T16:58:37.997051Z","created_at":"2026-10-14T15:22:15.640367Z","updated_at":"2026-10-14T16:58:37.999729Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/51543c6e-0d4b-4d56-b403-d772dc9cc157"},{"id":"58d65f8c-9bfe-4e0f-8026-f55da835720b","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Staff Machine Learning Engineer","slug":"staff-machine-learning-engineer-9c39e036","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 Staff Machine Learning Engineer, CX Intelligence \n  \n CEE Intelligence (CEEI) is the ML and intelligence layer for Coinbase's customer engagement ecosystem, building customer intelligence, evaluation systems, routing and classification models, safety guardrails, and decisioning capabilities that power Help Center, chat, voice, agent tooling, and other customer support runtimes. As a Staff Machine Learning Engineer, you'll lead the design and delivery of production ML systems across the org, shaping technical strategy, building scalable intelligence capabilities, and partnering with product and engineering stakeholders to improve resolution quality, automation coverage, safety, and customer experience. What you'll do: \n \n Own the design and delivery of production ML systems, applying LLMs, deep learning, graph neural networks, and classical ML techniques to solve complex customer experience problems.\n Partner with leadership and cross-functional stakeholders to define strategic roadmaps and translate vision into quarterly execution plans with measurable outcomes.\n Lead high-impact ML projects end-to-end, from architecture through production, managing priorities, risks, and dependencies.\n Build scalable, secure, and reliable ML systems, evaluation pipelines, and data workflows using high-quality, well-tested Python code.\n Mentor engineers and establish team-wide standards for design, testing, observability, and operational excellence.\n Drive design reviews covering security, responsible AI, model quality, and architectural integrity, improving reliability, scalability, and latency across the stack.\n \n Required Skills and Experience: \n \n 8+ years of experience in machine learning and software engineering, with proven success building, scaling, and maintaining production ML systems, data platforms, or analytical services.\n Hands-on expertise with one or more of LLMs, deep learning, graph neural networks, gradient-boosted trees, or regression, combined with strong knowledge of NLP, information retrieval, data mining, or advanced statistics.\n Strong Python skills with demonstrated ability to write maintainable, highly tested production code for ML services.\n Experience mentoring engineers and raising technical standards across a team or organization, including leading design reviews and influencing technical and non-technical stakeholders.\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n \n Job #: P77568\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 $218,025 — $256,500 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":218025,"salary_max":256500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","llm","nlp","deep-learning","search","machine-learning"],"apply_url":"https://www.coinbase.com/careers/positions/8267151?gh_jid=8267151","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T19:31:10Z","expires_at":"2026-11-13T16:58:01.54146Z","created_at":"2026-10-14T15:21:41.463785Z","updated_at":"2026-10-14T16:58:01.544331Z","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/58d65f8c-9bfe-4e0f-8026-f55da835720b"},{"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":"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":"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":"62316960-4081-4d09-883a-e1356f1a8463","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Senior AI Analyst, People Digital Solutions","slug":"senior-ai-analyst-people-digital-solutions-c64475e7","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n The People Operations \u0026 Digital Solutions team \n The People Operations \u0026 Digital Solutions team shapes the future of employee support at Okta through innovative technology, intelligent knowledge management, and automated self-service experiences. Reporting to the Senior Director, People Operations \u0026 Digital Solutions, this team collaborates closely with People Operations, Total Rewards, Recruiting, IT, Learning, and Knowledge Management to enhance digital support across the enterprise.\n The Senior AI Analyst opportunity \n We are seeking an experienced Senior AI Analyst with a strong background in ServiceNow and Analytics to help train, evaluate, and improve AI models and AI-powered enterprise solutions. The ideal candidate will combine hands-on ServiceNow knowledge, data and analytics expertise, and strong communication skills to create high-quality training data, evaluate AI outputs, and translate business and technical requirements into effective AI training scenarios. This is a high-impact role responsible for improving how employees interact with AI while enabling support teams through intelligent knowledge management and training.\n As the subject matter expert for our AI solutions, you will analyze conversational insights, optimize AI performance, and ensure AI assistants deliver accurate, relevant, and trusted responses. You'll own the training and continuous improvement of AI-powered experiences—including an employee support chatbot, Agentic Coach, and future AI assistants—while partnering with cross-functional teams to enhance knowledge, self-service, and employee support.\n What you’ll be doing  \n \n Train, test, and evaluate AI-powered assistants, chatbots, and agentic AI solutions to ensure accurate and reliable employee experiences.\n Design and optimize prompts, conversational flows, intents, responses, and training scenarios across enterprise support platforms.\n Evaluate AI outputs for accuracy, relevance, completeness, tone, and consistency while identifying and mitigating hallucinations, response gaps, or misinformation.\n Monitor and analyze AI performance metrics such as containment, resolution, user satisfaction, engagement, and escalation rates; identify trends, emerging intents, knowledge gaps, and opportunities for automation from conversational data.\n Apply ServiceNow knowledge to translate complex business processes into intuitive conversational scenarios, training data, and evaluation criteria; collaborate with ServiceNow administrators, developers, analysts, and business stakeholders to identify automation opportunities.\n Create and maintain AI training materials, test cases, evaluation criteria, and sample conversations; partner with Knowledge Management teams to improve content quality, discoverability, and AI readiness; keep materials current as products, processes, and policies evolve.\n Support testing and rollout of new AI capabilities and enhancements; provide insights and recommendations based on AI performance, user feedback, and analytics to drive continuous improvement across the People Organization.\n Stay current with developments in generative AI, prompt engineering, conversational AI, agentic AI, and responsible AI; contribute ideas that improve employee self-service and digital support experiences.\n \n What you’ll bring to the role \n \n Experience in AI training, prompt engineering, conversational design, NLP, or AI optimization within employee or customer support environments.\n Proven experience training, evaluating, and optimizing AI models, conversational agents, or LLM-powered assistants, including agentic AI solutions.\n Strong understanding of prompt engineering, AI evaluation, model optimization, and responsible AI practices.\n Demonstrated ability to analyze conversational data and performance metrics to drive measurable improvements.\n Working knowledge of ServiceNow or a similar enterprise service-management platform.\n Strong analytical skills and experience with tools such as SQL, Excel, Power BI, Tableau, or ServiceNow Analytics.\n Experience with enterprise conversational AI platforms, knowledge management systems, or AI-enabled search technologies.\n Excellent written and verbal communication skills with the ability to translate technical and business requirements into clear, user-focused content and influence cross-functional stakeholders.\n Understanding of knowledge management, digital employee support, and omnichannel service experiences.\n \n A","salary_min":108000,"salary_max":149000,"location":"Bellevue, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","llm","nlp","fine-tuning"],"apply_url":"https://www.okta.com/company/careers/opportunity/8257554?gh_jid=8257554","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T13:19:08Z","expires_at":"2026-11-13T16:58:07.274356Z","created_at":"2026-10-14T15:21:47.277821Z","updated_at":"2026-10-14T16:58:07.277552Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/62316960-4081-4d09-883a-e1356f1a8463"},{"id":"a91d5a21-3259-47d5-8df4-e146e013bc58","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Software Engineer, Intern - Labs (Summer 2027)","slug":"software-engineer-intern-labs-summer-2027-48ca1a56","description":"About Labs \n DoorDash Labs is an independent team within DoorDash. We're hiring software engineer interns to work at the intersection of software engineering and robotics to solve key business problems with elegant technical solutions. If you have a passion for applying robotics solutions to a service loved by millions of people, then we want to talk to you! \n About the Teams \n We are hiring Software Engineer interns across our Perception, Autonomy Platform, and DoorDash Air Cloud (Foundry) team. Please review the team descriptions below to learn about each. Selected candidates will be notified of which team is interested in pursuing their candidacy. \n   Perception: The Perception team helps Dot understand the world through vision foundation models and VLMs, supported by lidar and radar for safety. We tackle rare scenarios, adverse weather, and advances in reinforcement learning and end-to-end driving to make deliveries faster and smoother. We're seeking exceptional engineers in machine learning, computer vision, and state estimation to turn cutting-edge research into profitable autonomous delivery. Autonomy Platform: The Autonomy Platform team is responsible for the software foundation that Dot runs on. We build a wide variety of software frameworks for ensuring the robot operates reliably at an ever-increasing scale. This includes everything from designing the robot's operating system, building petabyte-scale data processing pipelines in the cloud, and optimizing nanosecond-level compute of bleeding-edge AI models. We are systems-oriented thinkers and hands-on builders who are excited to advance the state of the art in autonomy. Doordash Air Cloud (Foundry): The Air Cloud team, also known as Foundry, builds the cloud software that powers autonomous delivery across DoorDash—from the moment an order is placed and deemed eligible for drone or robot delivery, through merchant handoff, to flight management.   \n About the Role \n We believe interns are essential to our mission of attracting and retaining top talent. During our 12-week Software Engineer internship, interns are completely immersed in their teams and will have the opportunity to develop, maintain, and ship products. As an intern, you will directly impact our business by collaborating with your team to solve real problems for our customers.\n Applicants must be authorized to work in the U.S. to be considered for this position. F-1 students are eligible if they are using Curricular Practical Training (CPT). DoorDash does not support students on J-1 visas for internships at this time.\n The 2027 internship program will be hosted in person at a Doordash Labs office in either San Francisco or Sunnyvale Labs. You will have an opportunity to select your preferred location(s) and team preferences during the application process.\n You’re excited about this opportunity because you will… \n \n Develop, maintain and ship technical elements with the support of your mentor, manager, and team members\n Act on feedback, coaching, and mentorship from your mentor and team members\n Actively learn about the elements to which you contribute\n Make a direct impact on our business by collaborating with your team to solve problems for our customers\n Participate in intern programming - Leadership Speaker series, social events – virtually and in-person\n Present your summer learnings during a final presentation at the end of the internship\n You are excited about an in person summer work experience \n \n We’re excited about you because… \n \n You are pursuing a B.S. or M.S. Degree in Computer Science or equivalent, have no more than 2 years of full-time work experience, and are graduating between Fall 2027 to Summer 2028.\n You are available for a May or June 2027 start date (Internships are only hosted during the Summer)\n You have experience working with databases (e.g., AWS, SQL, etc.) \n You have a solid understanding of algorithms and data structures\n You have proficient experience working with at least 1 object-oriented programming language (e.g., Python, Java, Kotlin, etc.)\n You have experience writing clean code, working with version control, and doing unit testing. \n \n Preferred but not required  \n \n At least 1 previous Software Engineering internship or equivalent relevant experience\n Curiosity about and experience using AI-powered tools to support software development, problem solving, and learning, with an understanding of how to evaluate outputs and use these tools responsibly\n Ability to analyze and improve efficiency, scalability, and stability of various systems\n Excited to develop, release and run large-scale web applications\n Experience with solutions for systems monitoring, live deployments, and continuous integration\n Experience with real-time technology problems\n Experience working with service-oriented architecture, writing APIs, and designing systems.\n Participation in project or research-based technical work, hackathons, technical conferences/orga","salary_min":107400,"salary_max":158000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["computer-vision","healthcare","fine-tuning","generative-ai","cloud","robotics","reinforcement-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8263774","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T06:50:12Z","expires_at":"2026-11-13T17:03:28.756487Z","created_at":"2026-10-14T15:25:31.397968Z","updated_at":"2026-10-14T17:03:28.760236Z","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/a91d5a21-3259-47d5-8df4-e146e013bc58"},{"id":"5d06e771-bce8-47ec-ab25-c7a09a6ec39e","company_id":"545e1785-0a1e-478e-b21c-cb7ffa7e0b88","title":"Senior Machine Learning Engineer, Vehicle Perception","slug":"senior-machine-learning-engineer-vehicle-perception-6d396019","description":"Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.\n\nOur work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud \u0026 AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.\n\n\nTEAM\nThe Vehicle Perception team at Woven by Toyota tackles the core challenges of machine learning for 3D perception, sensor fusion, and computer vision in autonomous vehicles. Our work involves a variety of challenges, such as analyzing petabytes of multimodal driving data, solving optimization problems in computer vision, minimizing latency on hardware accelerators, deploying scalable and efficient machine learning (ML) training and evaluation pipelines, and designing novel neural network architectures to advance state-of-the-art ML for onboard perception. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with human-centered automated driving solutions for personal and commercial applications.\nWHO ARE WE LOOKING FOR?\nThe team is looking for a skilled Machine Learning Engineer to help advance a cutting-edge machine learning system for perception foundation models leveraging large-scale multimodal sensor data. You will have the chance to design and implement innovative machine learning models for our next-generation autonomous vehicle platform, influencing millions of Toyota production vehicles. We are looking for individuals who are passionate about self-driving car technology and its potential impact on humanity. Furthermore, we highly value candidates who exhibit a \"giver\" mindset, consistently seeking opportunities to assist their colleagues while maintaining a strong focus on delivering solutions to production.\n","salary_min":140000,"salary_max":230000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","deep-learning","autonomous-vehicles","computer-vision","machine-learning"],"apply_url":"https://jobs.lever.co/woven-by-toyota/68d72c7e-e867-45e8-b81b-3315889bea75/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T16:35:57.897Z","expires_at":"2026-11-13T17:00:18.00542Z","created_at":"2026-10-14T15:23:51.750868Z","updated_at":"2026-10-14T17:00:18.008985Z","company_name":"Woven by Toyota","company_slug":"woven-toyota","company_logo_url":"https://www.google.com/s2/favicons?domain=woven.toyota\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5d06e771-bce8-47ec-ab25-c7a09a6ec39e"},{"id":"bed4ba83-1003-483b-ae16-2e373644bf3e","company_id":"b6e5a3d1-9bde-4a82-8d78-9f38ed99ee81","title":"Staff Research Scientist - Foundation \u0026 World Models ","slug":"staff-research-scientist-foundation-world-models-95a79182","description":"As a Staff Research Scientist within Datadog AI Research (DAIR), you will drive research in foundation models and world models as a hands-on individual contributor. You will advance large-scale pre-training and multimodal learning across the diverse signals generated by distributed systems, including metrics, traces, logs, topology, and events. You will set the technical direction for ambitious research programs, raise the technical bar for the researchers and research engineers around you, and collaborate with Datadog's product and engineering teams to translate research advances into products. \n  \n What You'll Do: \n \n Drive research in foundation models, world models, and multimodal learning, shaping the technical direction of ambitious research programs grounded in observability\n Own research problems end to end, from framing the question through experimentation, model development, and evaluation\n Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities\n Advance approaches to pre-training, representation learning, world modeling, scaling, and evaluation for models that learn the dynamics of complex distributed systems\n Raise the technical bar across the team by reviewing research directions, mentoring researchers and research engineers, and setting standards for experimental rigor\n Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities\n Contribute to research publications, present at top-tier conferences such as NeurIPS, ICLR, and ICML, and help open-source key model artifacts and benchmarks\n \n  \n Who You Are: \n \n You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling\n You have driven technically ambitious research at meaningful scale as an individual contributor, whether in an industry research lab, startup, academic environment, or another research setting\n You have extensive hands-on experience designing, training, and evaluating large-scale deep learning models (such as large language models), with experience in multimodal or non-text data considered a strong plus\n You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements\n You set technical direction through influence rather than authority, and you have mentored other researchers or engineers and elevated the quality of work around you\n You want to stay deeply hands-on in research for the long term, and you can communicate complex research findings effectively across technical and non-technical audiences\n \n  \n Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. \n  \n About Datadog:  \n Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.\n  \n Equal Opportunity at Datadog: \n Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.\n  \n Your Privacy: \n Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice.\n  \n Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness rei","salary_min":320000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","healthcare","deep-learning","generative-ai","pre-training","search","llm","research"],"apply_url":"https://careers.datadoghq.com/detail/8261937/?gh_jid=8261937","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T16:34:19Z","expires_at":"2026-11-13T16:55:38.303397Z","created_at":"2026-10-14T15:19:28.521017Z","updated_at":"2026-10-14T16:55:38.306288Z","company_name":"Datadog","company_slug":"datadog","company_logo_url":"https://www.google.com/s2/favicons?domain=datadoghq.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bed4ba83-1003-483b-ae16-2e373644bf3e"},{"id":"154e5708-397b-4979-ab8e-aeaf950ea096","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Product Architect, AI (Auth0)","slug":"product-architect-ai-auth0-66afd6fe","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n Get to know Okta\n Okta is The World’s Identity Company. We free everyone to safely use any technology, anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth.\n At Auth0, an Okta company, we help organizations build secure, seamless customer experiences. As AI agents become active participants in software systems (acting on behalf of people, organizations, and other agents) identity becomes even more foundational. We are building for a future where agents can securely authenticate, access resources, delegate authority, and operate within clear, auditable boundaries.\n We’re building a world where Identity belongs to you.\n The Opportunity\n We are looking for a Product Architect, AI to help define how Auth0 and Okta lead the market in agentic identity, secure AI application development, and standards-based access for agents.\n This is a senior, highly strategic, and deeply hands-on role. You will work across Product, Engineering, Security, Developer Relations, Design, Go-to-Market, and our customer community to shape the technical and product direction for AI-native identity capabilities.\n You will bring a strong point of view on where the industry is going, grounded in real experience building AI-powered and agentic systems. You will help us translate fast-moving technical developments (including MCP, A2A, agentic commerce, delegated authorization, and emerging agent identity standards) into secure, practical product capabilities that customers can adopt with confidence.\n This role is for someone who enjoys moving between strategy and implementation: setting a long-term vision, designing platform primitives, engaging directly with customers and partners, contributing to standards and open source communities, and occasionally writing production-quality code or prototypes to prove what is possible.\n What you’ll be doing\n \n Define and evolve Auth0’s strategy for building, operating, and securing AI agents and agentic applications.\n Shape the product and technical strategy for agentic identity, including how agents authenticate, receive delegated authority, access resources, establish trust, and maintain auditable boundaries.\n Define approaches for securely exposing protected resources (including APIs, tools, data services, and MCP servers) to authorized agents.\n Partner closely with Product Management and Engineering leaders to turn strategic opportunities into clear product bets, architectural principles, product requirements, and durable platform capabilities.\n Help design and, where valuable, implement core identity capabilities that enable secure agent-to-resource and agent-to-agent interactions.\n Develop an informed perspective on emerging technologies and standards such as Model Context Protocol (MCP), agent-to-agent protocols, agentic commerce, AAuth, authorization frameworks, workload identity, and related specifications.\n Deep curiosity and a disciplined approach to staying ahead of the AI landscape, including foundation models, agent harnesses, AI frameworks, orchestration tools, evaluation and observability platforms, and rapidly evolving developer practices. You can distinguish durable shifts from short-lived hype and articulate their implications for customers, developers, and Auth0’s product strategy.\n Identify important industry shifts early, assess their implications for customers and the identity ecosystem, and communicate a clear point of view internally and externally.\n Work directly with strategic customers to understand their AI and identity architectures, uncover unmet needs, validate product direction, and help them build securely.\n Collaborate with Security, Legal, Privacy, and Trust teams to ensure that AI-related identity capabilities are secure, responsible, compliant, and usable in real-world enterprise environments.\n Represent Auth0 and Okta in the developer and identity communities through technical content, speaking engagements, customer conversations, standards participation, and open-source engagement.\n Build prototypes, reference implementations, and technical demonstrations using technologies such as Node.js, React, Python, and Go.\n Partner with Developer Relations and Go-to-Market teams to make complex identity and AI concepts approachable for developers, ","salary_min":208000,"salary_max":286000,"location":"Toronto, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","api-design","distributed-systems","generative-ai"],"apply_url":"https://www.okta.com/company/careers/opportunity/8261644?gh_jid=8261644","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T15:50:59Z","expires_at":"2026-11-13T16:58:07.269315Z","created_at":"2026-10-14T15:21:47.273734Z","updated_at":"2026-10-14T16:58:07.272504Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/154e5708-397b-4979-ab8e-aeaf950ea096"},{"id":"3d3c8e31-4a0a-44ba-bf8c-dcbc28aea9e1","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Product Architect, AI (Auth0)","slug":"product-architect-ai-auth0-60d325ea","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n Get to know Okta\n Okta is The World’s Identity Company. We free everyone to safely use any technology, anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth.\n At Auth0, an Okta company, we help organizations build secure, seamless customer experiences. As AI agents become active participants in software systems (acting on behalf of people, organizations, and other agents) identity becomes even more foundational. We are building for a future where agents can securely authenticate, access resources, delegate authority, and operate within clear, auditable boundaries.\n We’re building a world where Identity belongs to you.\n The Opportunity\n We are looking for a Product Architect, AI to help define how Auth0 and Okta lead the market in agentic identity, secure AI application development, and standards-based access for agents.\n This is a senior, highly strategic, and deeply hands-on role. You will work across Product, Engineering, Security, Developer Relations, Design, Go-to-Market, and our customer community to shape the technical and product direction for AI-native identity capabilities.\n You will bring a strong point of view on where the industry is going, grounded in real experience building AI-powered and agentic systems. You will help us translate fast-moving technical developments (including MCP, A2A, agentic commerce, delegated authorization, and emerging agent identity standards) into secure, practical product capabilities that customers can adopt with confidence.\n This role is for someone who enjoys moving between strategy and implementation: setting a long-term vision, designing platform primitives, engaging directly with customers and partners, contributing to standards and open source communities, and occasionally writing production-quality code or prototypes to prove what is possible.\n What you’ll be doing\n \n Define and evolve Auth0’s strategy for building, operating, and securing AI agents and agentic applications.\n Shape the product and technical strategy for agentic identity, including how agents authenticate, receive delegated authority, access resources, establish trust, and maintain auditable boundaries.\n Define approaches for securely exposing protected resources (including APIs, tools, data services, and MCP servers) to authorized agents.\n Partner closely with Product Management and Engineering leaders to turn strategic opportunities into clear product bets, architectural principles, product requirements, and durable platform capabilities.\n Help design and, where valuable, implement core identity capabilities that enable secure agent-to-resource and agent-to-agent interactions.\n Develop an informed perspective on emerging technologies and standards such as Model Context Protocol (MCP), agent-to-agent protocols, agentic commerce, AAuth, authorization frameworks, workload identity, and related specifications.\n Deep curiosity and a disciplined approach to staying ahead of the AI landscape, including foundation models, agent harnesses, AI frameworks, orchestration tools, evaluation and observability platforms, and rapidly evolving developer practices. You can distinguish durable shifts from short-lived hype and articulate their implications for customers, developers, and Auth0’s product strategy.\n Identify important industry shifts early, assess their implications for customers and the identity ecosystem, and communicate a clear point of view internally and externally.\n Work directly with strategic customers to understand their AI and identity architectures, uncover unmet needs, validate product direction, and help them build securely.\n Collaborate with Security, Legal, Privacy, and Trust teams to ensure that AI-related identity capabilities are secure, responsible, compliant, and usable in real-world enterprise environments.\n Represent Auth0 and Okta in the developer and identity communities through technical content, speaking engagements, customer conversations, standards participation, and open-source engagement.\n Build prototypes, reference implementations, and technical demonstrations using technologies such as Node.js, React, Python, and Go.\n Partner with Developer Relations and Go-to-Market teams to make complex identity and AI concepts approachable for developers, ","salary_min":226000,"salary_max":311000,"location":"Bellevue, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","generative-ai","api-design","distributed-systems","agents"],"apply_url":"https://www.okta.com/company/careers/opportunity/8110447?gh_jid=8110447","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T15:50:56Z","expires_at":"2026-11-13T16:58:07.264635Z","created_at":"2026-10-14T15:21:47.268966Z","updated_at":"2026-10-14T16:58:07.267452Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3d3c8e31-4a0a-44ba-bf8c-dcbc28aea9e1"},{"id":"02955c00-0f56-4cdd-826c-9e251d4a765b","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Director, Machine Learning Engineering, Ads Quality","slug":"director-machine-learning-engineering-ads-quality-2d657f9f","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 Pinterest is a visual discovery platform where hundreds of millions of people come to find inspiration and decide what to try, buy, or do next. Our Ads Quality organization builds the machine-learning systems that make ads relevant and valuable to Pinners while delivering meaningful outcomes for advertisers.\n We are seeking a Director of Machine Learning Engineering to lead a broad portfolio of Ads Quality modeling teams focused on engagement, conversion, ROAS optimization, ranking, representation learning, and ML-powered experimentation.\n In this role, you will shape and drive a unified technical strategy across Ads Quality, leading teams responsible for engagement ranking, oCPM and conversion modeling, ROAS optimization, lightweight ranking and retrieval models, foundation model adoption, sequence and multimodal modeling, and the quality and efficiency of production machine learning systems.\n  \n What you’ll do:  \n \n Set the technical vision and multi-year strategy for Ads Quality machine learning, connecting model innovation to Pinner value, advertiser performance, revenue, and marketplace health.\n Lead and develop a group of engineering managers, senior technical leaders, and machine-learning engineers across multiple modeling domains.\n Establish a coherent modeling roadmap across engagement, conversion, ROAS, relevance, ranking, and foundation-model initiatives.\n Drive improvements in model quality, calibration, generalization, cold-start performance, attribution, and robustness across Pinterest surfaces.\n Guide the evolution of Ads models toward larger, more generalizable architectures, including foundation models, distillation, long-context sequence modeling, multimodal representations, and cross-domain learning.\n Ensure that modeling investments translate into reliable production outcomes through strong offline evaluation, online experimentation, launch discipline, and post-launch monitoring.\n Partner closely with Ads Product, Ads Data Science, Ads Signals, Ads Retrieval, Ads Delivery, Measurement, Core, ATG, and ML Infrastructure.\n Set expectations for training-serving parity, data quality, privacy, reliability, latency, capacity, and cost efficiency.\n Improve engineering velocity through better experimentation workflows, reusable modeling infrastructure, automation, and agentic development tools.\n Build a culture of technical excellence, candid collaboration, inclusion, ownership, and continuous learning.\n Represent Ads Quality ML in senior leadership forums and communicate strategy, tradeoffs, risks, and results clearly to technical and non-technical audiences.\n \n  \n What we’re looking for: \n \n Minimum 12 years of experience building and deploying machine-learning systems, including significant experience leading managers and multi-team organizations.\n Demonstrated success leading large-scale recommendation, ranking, advertising, search, marketplace, or personalization ML teams.\n Strong understanding of modern deep-learning and recommender-system techniques, including sequence models, embeddings, multimodal models, multi-task learning, foundation models, distillation, and reinforcement learning.\n Experience with conversion, value, ROAS, bidding, or other lower-funnel optimization problems is strongly preferred.\n Proven ability to connect modeling objectives and offline metrics to online experiments and business outcomes.\n Experience operating production ML systems with demanding requirements for latency, availability, calibration, privacy, reliability, and cost.\n Strong judgment in balancing near-term product delivery with foundational technical investments.\n Track record of building high-performing organizations, developing senior leaders, and creating effective operating mechanisms.\n Excellent communication and collaboration skills, with the ability to inf","salary_min":314580,"salary_max":550515,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","agents","generative-ai","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8258175","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-06T21:30:23Z","expires_at":"2026-11-13T16:57:51.005164Z","created_at":"2026-10-14T15:21:31.271732Z","updated_at":"2026-10-14T16:57:51.008241Z","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/02955c00-0f56-4cdd-826c-9e251d4a765b"}],"page":1,"per_page":20,"total":1534,"total_is_exact":true,"total_pages":77}