{"has_next":true,"jobs":[{"id":"14a818b5-1068-4d53-8e01-2106c013d919","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Software Engineer, Operational/ Process Efficiency ","slug":"software-engineer-operational-process-efficiency-0675432b","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet. You will lead efforts to generalize complex depot operations—such as exterior cleaning, sensor calibration, and maintenance checks—using advanced robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to translate real-world needs into robust, working solutions.\n This role follows a hybrid work schedule and reports to a Director, Hardware and Sensors. \n You will: \n \n Drive the automation of the hardware lifecycle for critical sensors (lidar, radar, cameras) and compute modules.\n Develop and deploy agentic systems and foundation models to streamline workflows between internal teams and contract manufacturers.\n Identify opportunities to apply AI to manufacturing, installation, and troubleshooting processes to increase operational velocity.\n Interface with a diverse set of stakeholders, including hardware design engineers, failure analysis engineers, and diagnostic teams, to translate physical requirements into technical specifications.\n Bridge the gap between experimental ML models and high-scale production environments.\n \n You have: \n \n A Masters or PhD in Machine Learning, Computer Science, or a related technical field.\n A proven track record of delivering working engineering solutions, balancing scientific rigor with production needs.\n Experience in training, evaluating, and deploying machine learning models at scale.\n Strong communication skills and the ability to collaborate across multidisciplinary teams (from field technicians to hardware designers).\n \n We prefer: \n \n Hands-on experience or deep familiarity with agentic tools and frameworks.\n Experience working with large-scale foundation models (LLMs, VLMs) and fine-tuning them for specialized domains.\n Background in automating industrial or hardware-centric workflows.\n Familiarity with hardware diagnostics, failure analysis, or manufacturing processes.\n \n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $175,000 — $215,000 USD","salary_min":175000,"salary_max":215000,"location":"Mountain View, CA","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["agents","generative-ai","robotics","autonomous-vehicles","llm","reinforcement-learning","fine-tuning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=7926526","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T20:26:39Z","expires_at":"2026-06-29T14:04:30.317025Z","created_at":"2026-05-30T14:04:30.42607Z","updated_at":"2026-05-30T14:04:30.42607Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/14a818b5-1068-4d53-8e01-2106c013d919"},{"id":"8b3dbb78-3093-481e-9b0c-09e3ed1deb6e","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Principal Software Engineer, Data","slug":"principal-software-engineer-data-0cdb1bea","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Principal Software Engineers with backend experience to join our Data Platform Team (Data), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.\n What You'll Be Building \n \n Design \u0026 Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in scalable backend system design.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening and writing skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to design complex backend solutions, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $204,000 — $348,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials","salary_min":204000,"salary_max":348000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["cloud","pytorch","embeddings","robotics","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250071009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T19:39:54Z","expires_at":"2026-06-29T14:17:40.451966Z","created_at":"2026-05-30T14:17:40.562155Z","updated_at":"2026-05-30T14:17:40.562155Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8b3dbb78-3093-481e-9b0c-09e3ed1deb6e"},{"id":"f8a29ca5-91b9-4ad7-9236-f57043203a4b","company_id":"ff51c80a-dce9-4cb4-b2e6-9c060d25ef55","title":"Robotics Engineer, Technical Lead","slug":"robotics-engineer-technical-lead-f0a6b32f","description":"About Applied Intuition\n Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co .\n We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. \n About the role\n This is a founding technical role helping build and shape Applied Intuition’s robotics organization from the ground up. You will set the technical direction for robotics software and AI, write production code, and build functional demos on physical hardware from day one. The role is weighted heavily toward software and learned behaviors, with the expectation that you can engage meaningfully across the hardware stack when needed.\n At Applied Intuition, you will:\n \n Define and own the technical architecture for humanoid robotics software, spanning perception, planning, control, and learned behaviors\n Write production-quality code in Python and C++ and ship it to physical robots — this is a hands-on individual contributor role first\n Design, train, evaluate, and deploy learning-based policies for manipulation and locomotion\n Build functional demonstrations on multiple robot hardware platforms that prove out capabilities and inform the product roadmap\n Establish simulation infrastructure and validate behaviors in physics-based environments before deploying to hardware\n Instrument robots, analyze telemetry and failure data, and iterate quickly to improve robustness in real-world conditions\n Work with teleoperation and data collection pipelines to generate training data and close the sim-to-real gap\n Identify and recruit the next engineers on the team\n \n We're looking for someone who has:\n \n BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, or a related field, or equivalent hands-on experience\n 7+ years of experience in robotics software development, with a meaningful portion on physical humanoid, legged, or highly dexterous manipulation platforms\n Proven track record shipping learning-based systems — behavior cloning, RL, or VLA policies — to real robots in production or near-production settings\n Strong proficiency in Python and C++ for robotics and ML systems; experience with PyTorch or equivalent deep learning frameworks\n Deep understanding of robotics fundamentals: kinematics, dynamics, control theory, state estimation, and perception\n Experience building and evaluating visuomotor or multimodal policies end to end, from data collection through deployment\n Ability to operate independently in an early-stage environment, make architectural decisions with limited information, and build from scratch\n Comfort on the lab floor — debugging physical robots, running hardware-in-the-loop tests, and iterating on live systems\n \n Nice to have:\n \n Experience with state-of-the-art bi-dexterous mobile hardware platforms, including dexterous manipulation and whole body control\n Familiarity with hardware bring-up, sensor integration, or embedded systems; ability to engage with mechanical and electrical teams at a subsystem level\n Background in SLAM, 3D perception, or sensor fusion (IMU, lidar, cameras, force/torque)\n Experience with physics simulators such as MuJoCo, NVIDIA Isaac Sim, or Gazebo\n Familiarity with ROS/ROS2 or similar robotics middleware\n Publication record or open-source contributions in robot learning, embodied AI, or manipulation\n \n Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.\n Applied Intuition pay ranges reflect the ","salary_min":250000,"salary_max":400000,"location":"Sunnyvale, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["cloud","robotics","deep-learning","pytorch"],"apply_url":"https://boards.greenhouse.io/appliedintuition/jobs/4700425005?gh_jid=4700425005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T17:33:51Z","expires_at":"2026-06-29T14:03:36.517513Z","created_at":"2026-05-30T14:03:36.628511Z","updated_at":"2026-05-30T14:03:36.628511Z","company_name":"Applied Intuition","company_slug":"applied-intuition","company_logo_url":"https://www.google.com/s2/favicons?domain=appliedintuition.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f8a29ca5-91b9-4ad7-9236-f57043203a4b"},{"id":"78754b10-1caa-42cb-a933-ccfae8797f70","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Machine Learning Engineering Manager, App SW","slug":"machine-learning-engineering-manager-app-sw-5e031225","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n   The Role  \n We're looking for an exceptional leader to spearhead our new Application Engineering team, a self-sufficient and high-impact group focused on localising and advancing our autonomous driving technology for the US market. This is a unique opportunity to shape Wayve’s AV capabilities in the US from the ground up.\n As a founding manager, you’ll lead a small but mighty team of engineers working across robotics, machine learning, and systems integration. You'll drive development of autonomy features tailored for US's road infrastructure, cultural driving behaviours, and regulatory landscape, ensuring our AV stack performs safely and effectively in this highly distinctive environment.\n We’re looking for someone who thrives in self-directed, startup-like conditions, capable of setting a vision, executing fast, and making robust decisions independently — while staying aligned with global engineering efforts.\n This role requires breadth: strong experience across AV systems, including robotics and autonomy, is essential. If you also bring deep expertise in machine learning, that's a major plus.\n  \n Key Responsibilities: \n \n Build and lead a self-sufficient AV development team in the US, hiring and mentoring top talent across Robotics and ML.\n Deliver autonomy capabilities tailored to road conditions and driving norms, in close collaboration with central Autonomy teams.\n Drive full-cycle development: from identifying local autonomy needs, to designing, implementing, testing, and deploying features into production.\n Ensure the team upholds Wayve’s high engineering standards, while operating with agility and independence.\n Work closely with OEM partners in the US — representing Wayve’s autonomy team in technical discussions, capturing product requirements, and shaping joint development plans.\n Establish close working relationships with our product and vehicle operations teams in the US.\n \n About you  \n To be successful in this role, you'll bring strong technical expertise, proven leadership skills, and a passion for building robust autonomous systems that can adapt to diverse real-world challenges.\n Essential \n \n A strong background in robotics and autonomy, with experience building and deploying systems that operate in real-world environments.\n Demonstrated ability to lead and grow high-performing engineering teams, ideally in geographically distributed or independent settings.\n Comfortable with ambiguity: you can define goals, carve out roadmaps, and deliver high-impact work with minimal supervision.\n Broad technical fluency: capable of reviewing and guiding work across software engineering, ML, controls, and systems integration.\n Excellent communication skills: you’re able to clearly convey technical context and strategic vision across cultures and time zones.\n Strong product sense and stakeholder management skills: you’re comfortable interfacing directly with OEM customers and representing engineering in external-facing conversations. \n \n Desirable \n \n Prior experience in autonomous vehicles or robotic systems operating at scale.\n Familiarity with US's road environment, driving behaviour, or AV regulatory landscape.\n A strong foundation in machine learning and its application to real-time decision-making or perception systems.\n \n  \n This role is a full-time role based in Sunnyvale, CA  or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $336,400 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.  We operate core working hours so you can determine the schedule that works best for you and your team.  \n #LI-KM1 \n Wayve is committed to creatin","salary_min":336400,"salary_max":381600,"location":"Sunnyvale, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["generative-ai","autonomous-vehicles","robotics","machine-learning"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8571171002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T16:04:34Z","expires_at":"2026-06-29T14:12:44.929157Z","created_at":"2026-05-30T14:12:45.041753Z","updated_at":"2026-05-30T14:12:45.041753Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/78754b10-1caa-42cb-a933-ccfae8797f70"},{"id":"e0e00a39-c16a-434f-bfa5-59174ea0c816","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Machine Learning Engineering Manager, App SW","slug":"machine-learning-engineering-manager-app-sw-101e63ec","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n   The Role  \n We're looking for an exceptional leader to spearhead our new Application Engineering team, a self-sufficient and high-impact group focused on localising and advancing our autonomous driving technology for the US market. This is a unique opportunity to shape Wayve’s AV capabilities in the US from the ground up.\n As a founding manager, you’ll lead a small but mighty team of engineers working across robotics, machine learning, and systems integration. You'll drive development of autonomy features tailored for US's road infrastructure, cultural driving behaviours, and regulatory landscape, ensuring our AV stack performs safely and effectively in this highly distinctive environment.\n We’re looking for someone who thrives in self-directed, startup-like conditions, capable of setting a vision, executing fast, and making robust decisions independently — while staying aligned with global engineering efforts.\n This role requires breadth: strong experience across AV systems, including robotics and autonomy, is essential. If you also bring deep expertise in machine learning, that's a major plus.\n  \n Key Responsibilities: \n \n Build and lead a self-sufficient AV development team in the US, hiring and mentoring top talent across Robotics and ML.\n Deliver autonomy capabilities tailored to road conditions and driving norms, in close collaboration with central Autonomy teams.\n Drive full-cycle development: from identifying local autonomy needs, to designing, implementing, testing, and deploying features into production.\n Ensure the team upholds Wayve’s high engineering standards, while operating with agility and independence.\n Work closely with OEM partners in the US — representing Wayve’s autonomy team in technical discussions, capturing product requirements, and shaping joint development plans.\n Establish close working relationships with our product and vehicle operations teams in the US.\n \n About you  \n To be successful in this role, you'll bring strong technical expertise, proven leadership skills, and a passion for building robust autonomous systems that can adapt to diverse real-world challenges.\n Essential \n \n A strong background in robotics and autonomy, with experience building and deploying systems that operate in real-world environments.\n Demonstrated ability to lead and grow high-performing engineering teams, ideally in geographically distributed or independent settings.\n Comfortable with ambiguity: you can define goals, carve out roadmaps, and deliver high-impact work with minimal supervision.\n Broad technical fluency: capable of reviewing and guiding work across software engineering, ML, controls, and systems integration.\n Excellent communication skills: you’re able to clearly convey technical context and strategic vision across cultures and time zones.\n Strong product sense and stakeholder management skills: you’re comfortable interfacing directly with OEM customers and representing engineering in external-facing conversations. \n \n Desirable \n \n Prior experience in autonomous vehicles or robotic systems operating at scale.\n Familiarity with US's road environment, driving behaviour, or AV regulatory landscape.\n A strong foundation in machine learning and its application to real-time decision-making or perception systems.\n \n  \n This role is a full-time role based in Sunnyvale, CA  or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $336,400 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.  We operate core working hours so you can determine the schedule that works best for you and your team.  \n #LI-KM1 \n Wayve is committed to creatin","salary_min":336400,"salary_max":381600,"location":"Detroit","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["robotics","generative-ai","autonomous-vehicles","machine-learning"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8568364002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T16:04:33Z","expires_at":"2026-06-29T14:12:45.00829Z","created_at":"2026-05-30T14:12:45.119737Z","updated_at":"2026-05-30T14:12:45.119737Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e0e00a39-c16a-434f-bfa5-59174ea0c816"},{"id":"0d7d0e83-e4e7-436c-8ea8-9998eef08a01","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Android","slug":"helix-ai-engineer-android-4b9829bf","description":"Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose and require 5 days/week in-office collaboration. It’s time to build.\n We're looking for a Senior Android Engineer with deep expertise in low-level Android systems, the NDK, and real-time sensor and video pipelines. This is not a standard Android app role — you'll be building the mobile application that interfaces directly with our custom sensor hardware over USB, ingests high-frequency camera and IMU data in real time, and runs on-device AI inference at the edge.\n If you've spent time below the Java/Kotlin layer — writing C/C++ via the NDK, implementing custom HALs, or building zero-copy sensor pipelines — this role was built for you.\n WHAT YOU'LL DO \n \n Build and own the Android application that serves as the primary mobile interface to Figure's humanoid robots, connected via USB Host / Android Open Accessory protocols.\n Architect high-throughput, zero-drop data ingestion pipelines for high-FPS image sensors and high-frequency IMU data, using zero-copy memory techniques and real-time concurrency models.\n Implement custom hardware abstraction layers (HAL) and leverage the Android NDK (C/C++) for high-performance, low-latency processing.\n Optimize CPU/GPU workloads for real-time edge filtering under strict thermal and battery constraints, using foreground services and WorkManager for bulletproof background operation.\n Integrate on-device AI inference libraries (TFLite, MediaPipe, ONNX Runtime, OpenCV) for real-time computer vision and sensor fusion.\n Implement low-latency video streaming protocols (e.g. WebRTC) \n \n WHAT WE'RE LOOKING FOR \n \n Deep expertise in Android NDK (C/C++) — custom HAL development, USB Host/AOA protocol communication, and direct hardware interfacing below the standard SDK layer.\n Proven experience architecting real-time, low-latency data pipelines for high-bandwidth sensors — zero-copy memory, real-time concurrency, and synchronization with zero frame drops.\n Mastery of Android system resource management: CPU/GPU workload optimization, thermal and battery constraints, foreground services, and WorkManager.\n Strong proficiency in both C/C++ (NDK) and Kotlin/Java for Android.\n Experience shipping production Android applications in hardware-connected, latency-critical environments.\n Proven track record shipping and maintaining production Android applications at scale — including crash rate management, OTA update rollout strategies, real-time telemetry and monitoring pipelines, and sustaining reliability across a large, diverse active user base spanning multiple device configurations and Android OS versions\n \n NICE TO HAVE \n \n Experience integrating on-device CV/ML inference: TensorFlow Lite, MediaPipe, ONNX Runtime, or OpenCV applied to raw sensor feeds.\n Familiarity with WebRTC or other low-latency streaming protocols for real-time video.\n Background in DSP techniques applied directly to raw sensor data.\n Prior work in robotics companion apps, industrial Android devices, AR/computer vision mobile apps, automotive HMI, or drone control applications.\n \n The US base salary range for this full-time position is between $150,000 - $400,000 annually.\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":150000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","robotics","tensorflow","computer-vision","mobile"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4685209006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T22:27:59Z","expires_at":"2026-06-29T14:05:53.434799Z","created_at":"2026-05-29T14:18:08.419145Z","updated_at":"2026-05-30T14:05:53.546009Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0d7d0e83-e4e7-436c-8ea8-9998eef08a01"},{"id":"a944334e-23f0-4033-b1c8-307c9e7c7124","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Backend Infrastructure ","slug":"helix-ai-engineer-backend-infrastructure-13269072","description":"Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose and require 5 days/week in-office collaboration. It’s time to build.\n We're looking for a senior-level backend engineer who has scaled high-throughput, low-latency data systems and has strong instincts around cloud infrastructure and real-time streaming pipelines. You'll architect and build the core backend systems that power Figure's real-time data infrastructure — enabling the scale and reliability that our AI and robotics platforms depend on.\n This is a high-ownership role at the intersection of media and sensor data streaming, cloud systems, and applied ML serving. You'll work closely with our AI and robotics teams to ensure latency, reliability, and throughput meet the demands of real-world robot operation.\n WHAT YOU'LL DO \n \n Architect and scale cloud backend infrastructure for high-concurrency, real-time streaming of media and sensor data across robot fleets and user sessions.\n Design and build low-latency data pipelines that ingest, route, and process high-bandwidth streams — including camera feeds, IMU data, and other robot sensor outputs — into our AI stack in real time.\n Own reliability, latency, and throughput SLAs for streaming and data infrastructure.\n Collaborate with AI and robotics teams to integrate ML model serving into real-time data pipelines.\n Build observability, alerting, and tooling to give the team full situational awareness over live robot traffic.\n Drive architectural decisions and mentor engineers across the team.\n \n WHAT WE'RE LOOKING FOR \n \n Deep experience scaling cloud backend systems handling high-concurrency, real-time data streams — media, sensor, telemetry, or equivalent high-bandwidth pipelines.\n Strong fundamentals in distributed systems: stream processing, connection management, data transport, and low-latency architecture.\n Proficiency in one or more backend languages (Go, C++, Python, Rust) and cloud platforms (AWS, GCP, or Azure).\n Experience with containerized infrastructure, service mesh, and large-scale deployment pipelines.\n Strong communication and cross-functional collaboration skills.\n \n NICE TO HAVE \n \n Hands-on experience integrating AI inference serving (Triton Inference Server, TensorRT, SageMaker, or similar) into real-time data pipelines.\n Background in robotics, autonomous vehicles, live media platforms, or other latency-critical streaming domains.\n Familiarity with protocols such as WebRTC, RTSP, gRPC, or Kafka for real-time data transport.\n Experience with on-device or edge inference and the tradeoffs of cloud vs. edge processing.\n \n The US base salary range for this full-time position is between $150,000 - $400,000 annually.\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":150000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["robotics","mlops","api-design","autonomous-vehicles","cloud","gpu","data-pipeline","distributed-systems"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4685172006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T21:42:25Z","expires_at":"2026-06-29T14:05:53.514412Z","created_at":"2026-05-29T14:18:08.491663Z","updated_at":"2026-05-30T14:05:53.629497Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a944334e-23f0-4033-b1c8-307c9e7c7124"},{"id":"88b5244c-2383-4f06-b5ef-0ade11296098","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Technical Lead Manager, Prediction \u0026 Planning, Machine Learning Eval","slug":"staff-technical-lead-manager-prediction-planning-ml-eval-29b43259","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver’s behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently. \n We have an exciting opportunity for a Staff Technical Lead Manager to lead our ML Evaluation team. In this role, you will define the strategic vision for our evaluation platforms, scaling the critical infrastructure and metrics required, and partner closely with the modeling teams to rigorously validate our next-generation deep neural networks and accelerate ML developer velocity across PrePlan.\n You will: \n \n Influence the strategic direction of foundational infrastructure and evaluation platforms to robustly support next-generation ML model evaluation use cases\n Collaborate cross-functionally with ML engineers, data scientists, and infrastructure teams to identify, define, and surface critical signals on model, component, and system-level performance\n Leverage and scale evaluation and infrastructure platforms to significantly enhance the ML developer experience, enabling faster iteration through earlier, more reliable, and trusted model evaluation\n Manage and mentor a focused team of engineers, aligning their career growth and aspirations with critical organizational needs\n Drive best practices and leverage deep technical awareness of the Alphabet ML stack (e.g., TensorFlow, JAX, Flax, Apache Beam) to optimize evaluation workflows\n Stay at the forefront of emerging technologies, industry trends, and research in ML evaluation methodologies and advanced metrics design\n \n You have:  \n \n M.S. in Computer Science, Mathematics, or equivalent industry experience in Robotics or large-scale ML systems with critical evaluation needs\n 5+ years of experience building and maintaining large-scale distributed infrastructure, ML inference systems, or evaluation platforms, including 3+ years of engineering management experience\n Strong coding and testing proficiency, specifically in Python and C++\n Strong foundational knowledge of model evaluation and core data science principles (e.g., confidence intervals, outlier identification, curve fitting, and causality analysis)\n Familiarity with large-scale ML deployment and orchestration tools (e.g., TF Serving, TorchServe, Kubeflow, SageMaker Pipelines, or Vertex AI Pipelines)\n Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow\n \n We prefer: \n \n Experience developing and maintaining evaluation pipelines for ML models\n Experience deploying and supporting machine learning models for computer vision, natural language processing, robotics/motion planning, or recommendation systems\n Experience supporting a small team of MLEs developing high-capacity, production-grade models and components\n Strong understanding of metrics computation and regression detection at scale\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["robotics","nlp","computer-vision","pytorch","autonomous-vehicles","deep-learning","tensorflow","evaluation"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=7963516","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T17:26:50Z","expires_at":"2026-06-29T14:04:32.30248Z","created_at":"2026-05-29T14:12:24.077985Z","updated_at":"2026-05-30T14:04:32.417838Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/88b5244c-2383-4f06-b5ef-0ade11296098"},{"id":"6dc81f39-064c-435f-95c1-b6c70be6a1c5","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Machine Learning Engineer, App SW","slug":"machine-learning-engineer-app-sw-73eaf56f","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The Role  \n As an  ML Engineer  within the Application Engineering team, you’ll lead critical initiatives that push the frontier of model-based autonomous driving—both in terms of core driving performance and feature-level intelligence such as personalisation, comfort, and collaboration.\n You’ll design and deliver ML-driven behaviors that scale from assisted to autonomous driving. Your work will span across model architecture, data pipelines, evaluation frameworks, and real-world deployment. You’ll collaborate deeply with AI Platform, Simulation, Robot SW and Model Release teams to build systems that are performant, adaptable, and ready for production.\n Responsibilities:\n \n Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization.\n Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment.\n Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness.\n Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development.\n Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems.\n Collaborate cross-functionally across various teams to ensure integration and iteration velocity.\n Mentor senior engineers and shape the long-term technical direction across Autonomy.\n \n About you:  \n In order to set you up for success as a Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n Essential\n \n Extensive and proven track record of shipping deep learning systems to production.\n Expert in deep learning (esp. sequential models, control, planning, or perception).\n Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.\n Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components.\n Ability to lead technical initiatives across teams, drive alignment, and mentor engineers.\n \n Desirable\n \n Prior work in autonomous driving, imitation learning, or trajectory prediction.\n Familiarity with personalization, human behavior modeling, or driver intent inference.\n Experience integrating ML systems into production hardware or multi-agent simulation.\n \n This role is a full-time role based in Sunnyvale or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $283,500 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.  \n #LI-KM1 \n Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. \n We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition  (including breastfeeding) or any other ba","salary_min":283500,"salary_max":381600,"location":"Detroit","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","data-pipeline","robotics","pytorch","generative-ai","deep-learning","gpu","agents"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8568694002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T14:51:17Z","expires_at":"2026-06-29T14:12:44.75073Z","created_at":"2026-05-29T14:50:38.39389Z","updated_at":"2026-05-30T14:12:44.866872Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6dc81f39-064c-435f-95c1-b6c70be6a1c5"},{"id":"2f82717a-ca5c-44ec-afbc-871db9888784","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Director, Data Science","slug":"director-data-science-e0c2bfe0","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n Job Summary \n May Mobility is entering an exciting phase of growth as we expand our autonomous transit and mobility services across the country. Founded in 2017 by a team of experienced roboticists, perception, behavior, AI, and software engineers, we operate driverless transit shuttles in real communities — not as a research demonstration, but as a daily-service product that people rely on to get to work, school, and home.\n The Director, Data Science will lead the team responsible for turning the data generated by our fleet, simulation environment, and ML systems into the insights, evaluations, and decisions that make our autonomous service safer, more efficient, and ready to scale into new cities. You will own data science across simulation and synthetic data, perception and planning ML evaluation, fleet operations analytics, and the data infrastructure that supports them. You will partner directly with Engineering, Product, Operations, and Safety leadership to set measurement standards, define release criteria, and translate frontline operating data into the next generation of our autonomy stack.\n This is a leadership role for someone who has scaled a data science function inside a hard-tech environment, who is comfortable making engineering and product tradeoffs alongside their team, and who sees the gap between research-grade ML and production transit-grade ML as the most interesting problem in the industry today.\n Essential Responsibilities \n \n Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform that supports them; translate that strategy into a 12–24 month roadmap with measurable milestones.\n Lead, grow, and develop a team of senior data scientists, ML engineers, and front-line managers; recruit from a small expert pool, calibrate the bar, and build a hiring brand that allows May Mobility to win against AV, robotics, and AI competitors.\n Partner with Engineering, Product, Safety, and Operations leaders to define release criteria, performance metrics, and ODD-expansion gates; use data to make the business case for what we deploy, where, and when.\n Drive ML and analytics applications end-to-end: dataset curation, scenario coverage, modeling, offboard evaluation, productionization, and continuous monitoring of fleet performance in the wild.\n Establish measurement and experimentation standards across the company — including before/after analyses for stack changes, A/B-style comparisons in simulation, and statistically credible reporting on real-world incidents.\n Lead team-wide quality activities including design and code reviews; hold the bar on engineering rigor for production data science systems.\n Track and trend technical performance of the autonomy stack in the field; surface root causes, prioritize fixes with engineering, and represent fleet-data findings to executives, regulators, and partners.\n Provide technical guidance to Engineering and Operations leaders on issue diagnosis, resolution, and the ML changes most likely to move our key safety and service metrics.\n Represent May Mobility's data science work externally where appropriate — through publications, conference talks, partner reviews, and recruiting.\n \n Skills and Abilities \n Success in this role typically requires the following competencies: \n \n Autonomy Data Expertise. Can reason fluently about the data produced by a modern AV stack — sensor logs, perception outputs, planning traces, simulator results, and operational telemetry — and can identify which signals matter for which decisions.\n Hands-On Technical Depth. Has personally shipped production ML or analytics systems within the last 3–5 years and is credible in code review and design review with senior engineers and scientists.\n Cross-Functional Translator. Can explain a complex ML or statistical finding to engineering, product, and executive audiences; and ","salary_min":217000,"salary_max":312000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["robotics","healthcare","distributed-systems","pytorch","computer-vision","tensorflow","reinforcement-learning","autonomous-vehicles"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8561428002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T21:54:47Z","expires_at":"2026-06-29T14:17:06.3175Z","created_at":"2026-05-28T14:18:43.046233Z","updated_at":"2026-05-30T14:17:06.431533Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2f82717a-ca5c-44ec-afbc-871db9888784"},{"id":"fa191a7a-632b-472c-acb7-b7360a7925f8","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director, Prediction and ML Planning","slug":"director-prediction-and-ml-planning-360f2a66","description":"About Motional: \n Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation. Mission Summary: \n Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.\n As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion. Core Responsibilities: \n \n Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.\n Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. \n Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.\n Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards. \n \n Required Qualifications \u0026 Experience: \n \n Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.\n Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.\n ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.\n Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.\n Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs) .\n Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning. \n \n Preferred Qualifications: \n \n Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.\n A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.\n Experience building large-scale data pipelines and training infrastructure required to train large driving models.\n \n \n  We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote. \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Rang","salary_min":288000,"salary_max":396000,"location":"Remote (US)","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","llm","reinforcement-learning","robotics","data-pipeline"],"apply_url":"https://motional.com/open-positions/?gh_jid=7749539003#/7749539003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T14:37:33Z","expires_at":"2026-06-29T14:05:57.689923Z","created_at":"2026-05-28T14:07:27.811425Z","updated_at":"2026-05-30T14:05:57.80649Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fa191a7a-632b-472c-acb7-b7360a7925f8"},{"id":"a81eda03-7e82-45be-919e-39f563f2c24d","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director, Prediction and ML Planning","slug":"director-prediction-and-ml-planning-ec32b5bd","description":"About Motional: \n Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation. Mission Summary: \n Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.\n As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion. Core Responsibilities: \n \n Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.\n Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. \n Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.\n Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards. \n \n Required Qualifications \u0026 Experience: \n \n Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.\n Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.\n ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.\n Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.\n Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs) .\n Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning. \n \n Preferred Qualifications: \n \n Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.\n A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.\n Experience building large-scale data pipelines and training infrastructure required to train large driving models.\n \n \n  We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote. \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Rang","salary_min":288000,"salary_max":396000,"location":"Pittsburgh, PA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","autonomous-vehicles","robotics","llm","data-pipeline"],"apply_url":"https://motional.com/open-positions/?gh_jid=7749537003#/7749537003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T14:37:33Z","expires_at":"2026-06-29T14:05:57.776906Z","created_at":"2026-05-28T14:07:27.895574Z","updated_at":"2026-05-30T14:05:57.889935Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a81eda03-7e82-45be-919e-39f563f2c24d"},{"id":"3fa85144-87ad-48b5-b151-9737480face6","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director, Prediction and ML Planning","slug":"director-prediction-and-ml-planning-ecc5bb9c","description":"About Motional: \n Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation. Mission Summary: \n Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.\n As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion. Core Responsibilities: \n \n Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.\n Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. \n Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.\n Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards. \n \n Required Qualifications \u0026 Experience: \n \n Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.\n Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.\n ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.\n Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.\n Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs) .\n Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning. \n \n Preferred Qualifications: \n \n Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.\n A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.\n Experience building large-scale data pipelines and training infrastructure required to train large driving models. \n \n  We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote. \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Range","salary_min":288000,"salary_max":396000,"location":"Boston, MA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","reinforcement-learning","llm","autonomous-vehicles","robotics"],"apply_url":"https://motional.com/open-positions/?gh_jid=7749522003#/7749522003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T14:37:32Z","expires_at":"2026-06-29T14:05:57.612382Z","created_at":"2026-05-28T14:07:27.983518Z","updated_at":"2026-05-30T14:05:57.722175Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3fa85144-87ad-48b5-b151-9737480face6"},{"id":"77cc20d9-b485-408a-9a85-753c8c333d3c","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, App","slug":"senior-software-engineer-app-e60d648a","description":"Your Impact at LILA Scientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality — and we need engineers who want to solve problems no one has solved before.\n We're hiring Sr Principal / Principal Software Engineers to design the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI.\n About The Team \n The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results.\n \n AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons.\n The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them.\n You'll learn domains you never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your technical surface area grows fast.\n You'll ship things that matter. The tools you build accelerate research timelines from months to days.\n \n If you want to build at the intersection of AI and science, move fast without breaking trust, and grow into the kind of engineer who can architect systems that don't exist yet — we want to talk.\n \n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Applied AI Engineering: Experience building with AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks.\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware drivers.\n \n \n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to","salary_min":144000,"salary_max":240000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","pytorch","robotics","data-pipeline","llm","embeddings","cloud","rag"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4248042009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:55:46Z","expires_at":"2026-06-29T14:17:43.519875Z","created_at":"2026-05-27T14:18:34.581118Z","updated_at":"2026-05-30T14:17:43.627321Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/77cc20d9-b485-408a-9a85-753c8c333d3c"},{"id":"83ca8ffa-09ac-4942-a639-4e6c4b482642","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Operations Research","slug":"senior-software-engineer-operations-research-e517b660","description":"Your Impact at LILA \n We are a cross-functional team (Software and Robotics) developing orchestration algorithms (instrument scheduling and robot routing) and lab simulation capabilities. We are building the muscles of the lab, which translate the AI brain's ideas into efficient robotic movements. Our work involves building data pipelines to feed the orchestration algorithms. We work with robotics scientists to build and deploy the algorithms on our software platform and ensure they meet scientific constraints.\n We are seeking a Senior Software Engineer, Operations Research to join our software group and help build the next generation AI-driven scientific platform. In this role, you will design, build, and optimize backend systems and data infrastructure that power orchestration and lab execution. You will focus on developing services, high-performance APIs, databases, and ensuring the reliability of systems that integrate advanced AI frameworks with complex scientific workflows.\n You'll work closely with robotics researchers, platform engineers, and scientists to develop systems that can handle diverse workloads and scale to demanding throughput. This is an opportunity to apply your engineering expertise to a cutting-edge AI platform with real scientific impact. If you are passionate about building performant and elegant systems, we would love to hear from you.\n What You'll Be Building \n \n (Fleet) orchestrator, Scheduler, Manufacturing Execution System, data pipelines, and related software systems.\n Design \u0026 Build APIs: Design and build APIs and backend services that integrate with AI-driven applications, with focus on reliability and performance.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Build and deploy production-grade systems on AWS using Kubernetes and modern DevOps practices.\n Cross-Functional Collaboration: Work with robotics scientists, platform engineers, and ML teams to integrate data pipelines and orchestration into scientific workflows.\n \n What You'll Need to Succeed \n \n Bachelor's or Master's degree in Computer Science, Engineering, or related field.\n 5–10 years of engineering experience building and deploying large-scale backend or data systems in production.\n Backend / Data Development: Experience developing distributed software and data systems (Postgres, Flyte, Temporal, NATS/MQTT, FastAPI).\n Hands-on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Experience developing scheduling software or manufacturing execution systems.\n Experience with operations research solvers (OR-Tools, HiGHS, Gurobi).\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Familiarity with Python for Science: Familiarity with data science, data visualization, and ML libraries (pandas, polars, numpy, scipy, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $180,000 — $256,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA bui","salary_min":180000,"salary_max":256000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["pytorch","robotics","cloud","data-pipeline","embeddings","research"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4246973009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:46Z","expires_at":"2026-06-29T14:17:43.904427Z","created_at":"2026-05-27T14:18:35.008145Z","updated_at":"2026-05-30T14:17:44.01629Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/83ca8ffa-09ac-4942-a639-4e6c4b482642"},{"id":"25353da4-ae66-4acf-b4b6-fea4e00fda29","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Data","slug":"senior-software-engineer-data-e29e2009","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Data Platform Team (Data), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.\n What You'll Be Building \n \n Design \u0026 Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale backend systems in production.\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $144,000 — $288,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values ","salary_min":144000,"salary_max":288000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["robotics","data-pipeline","pytorch","cloud","embeddings"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250077009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:23Z","expires_at":"2026-06-29T14:17:43.668505Z","created_at":"2026-05-27T14:18:34.759394Z","updated_at":"2026-05-30T14:17:43.783774Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/25353da4-ae66-4acf-b4b6-fea4e00fda29"},{"id":"4ba5f31d-5017-4850-9d40-5a3c0331575c","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Lab Software","slug":"senior-software-engineer-lab-software-347521f8","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Lab Software Team (LaS), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.\n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields.\n Lab Automation Experience: Experience with laboratory devices, robotics, or hardware drivers.\n Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $144,000 — $210,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd ","salary_min":144000,"salary_max":210000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["embeddings","data-pipeline","robotics","cloud"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250038009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:02Z","expires_at":"2026-06-29T14:17:43.749222Z","created_at":"2026-05-27T14:18:34.838741Z","updated_at":"2026-05-30T14:17:43.859766Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ba5f31d-5017-4850-9d40-5a3c0331575c"},{"id":"1e411b32-416c-4234-bcb3-3604b204f141","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Staff Machine Learning Engineer, AV Core","slug":"staff-machine-learning-engineer-av-core-1f2ae697","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Staff Machine Learning Engineer on Wayve’s Core Model Safety team in AV Core, you will help shape what our end-to-end driving model must understand to be safe and reliable in the real world - and turn that into trained capabilities, clear evidence, and adoption on the shared backbone across core and product engineering.\n  \n The Core Model Safety team builds foundational capabilities for assisted and automated driving - collision avoidance, scene understanding, model understanding, and robustness under failure. You will work in a focused, high-impact senior team with strong ownership, access to large-scale training and fleet data, and close partners in research, simulation, evaluation, and applied engineering.\n  \n Key responsibilities \n \n Drive Core Model Safety roadmap themes owning the full lifecycle from research to offline/online experiments to technology transfer.\n Train and deploy end-to-end AV 2.0 models on our global fleet, using large-scale, diverse data to validate capabilities and improve generalisation across vehicles, markets, and driving conditions.\n Build high-value open-loop and closed-loop evaluations for core capabilities and representation learning.\n Align priorities and learn from the organisation - with AV Core, Evaluation, and Product Engineering on roadmaps and failure modes; from fleet, simulation, and product feedback; and through mentoring others on the team.\n Maintain awareness of the wider business context - division and company priorities, near-term product programmes, and how Core Model Safety work enables them.\n \n About you   \n In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n  \n Essential  \n \n 5+ years in ML engineering, including pathfinding in ambiguous problems - from scoping and evals to establishing a direction (and knowledge transfer) for others to build on.\n Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.\n Hands-on experience with transformer-based and multimodal architectures, including vision-language models (VLM), vision-language-action models (VLA), or equivalent.\n Hands-on experience training shared representations with multiple tasks or objectives (multi-stage or joint training), including real trade-offs across data and losses.\n Staff-level technical leadership: research-literate and pragmatic, setting direction, raising the bar, and leading cross-functional work without formal line management.\n \n  \n Desirable  \n \n Prior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systems.\n Experience in 3D scene understanding and representation learning for geometric and semantic perception, large-scale semantic enrichments.\n Experience in reward modelling, behaviour modelling, model introspection, and/or interpretability.\n Experience with redundant or fallback architectures, safety-critical systems.\n Experience across foundations/pretraining and applied engineering teams; large-scale training infrastructure and/or agentic workflows.\n \n This is a full-time role based in our office in Sunnyvale.  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $336,400 to $370,300, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. \n We understand that everyone has a unique set of skills and experiences and that no","salary_min":336400,"salary_max":370300,"location":"Sunnyvale, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["generative-ai","autonomous-vehicles","agents","robotics","pytorch","reinforcement-learning","gpu","pre-training"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8562545002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T19:02:03Z","expires_at":"2026-06-29T14:12:48.484991Z","created_at":"2026-05-27T14:13:12.451192Z","updated_at":"2026-05-30T14:12:48.600908Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1e411b32-416c-4234-bcb3-3604b204f141"},{"id":"731f6d0a-ba12-48e0-98c0-e09482be412c","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Computer Vision Engineer","slug":"computer-vision-engineer-c1d0ac4d","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n About the Role\n We are seeking a  Computer Vision Engineer to join our Perception team at Anduril Industries, where we develop cutting-edge perception systems for autonomous drones and unmanned sea vehicles in defense applications. While our team has strong capabilities in machine learning and real-time processing, we need a classical computer vision expert to elevate our camera integration, calibration workflows, and establish industry-standard best practices. This role will collaborate across multiple teams, supporting ML engineers, system architects, and integration specialists by ensuring our perception systems receive high-quality, well-calibrated sensor data from diverse camera modalities.\n Key Responsibilities\n Camera Systems \u0026 Integration\n \n Design and implement camera integration pipelines for diverse sensor modalities including RGB, stereo, fisheye, thermal, and event-based camera\n Develop middleware and vision pipeline components that interface with our perception stack\n Work with hardware and program teams to evaluate and integrate new camera systems\n \n Calibration \u0026 Geometric Vision\n \n Develop and maintain calibration procedures for intrinsic and extrinsic camera parameters\n Implement multi-camera calibration systems and camera-lidar extrinsic calibration workflows\n Design online and offline calibration methods for field deployment scenarios\n Apply geometric computer vision techniques including structure from motion and 3D reconstruction\n \n Classical Computer Vision\n \n Implement robust image processing pipelines (filtering, augmentation, rectification)\n Develop feature detection, matching, and tracking algorithms\n Design optical flow and visual odometry solutions\n Optimize vision algorithms for real-time performance on embedded platforms\n \n Standards \u0026 Best Practices\n \n Establish and document computer vision best practices\n Create reusable calibration tools and frameworks\n Ensure vision systems meet defense industry standards and requirements\n Conduct lab testing and validation of camera systems\n \n Required Qualifications\n \n Education : Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or related field\n Experience : 4-6 years of industry experience in computer vision engineering OR Master's degree with 2-4 years of industry experience\n Strong proficiency in C++ or Python\n Hands-on experience with OpenCV and classical computer vision algorithms\n Deep understanding of camera models, calibration theory, and geometric vision\n Experience with multi-camera systems and sensor fusion\n Experience developing middleware and vision pipelines (ROS/ROS2 or similar)\n Familiarity with diverse camera technologies (RGB, stereo, fisheye, thermal, ToF, event-based)\n Lab experience with camera systems and optical equipment\n \n Preferred Qualifications\n \n Rust programming experience\n Master's degree in Computer Vision, Robotics, or related field\n Experience in defense, aerospace, or autonomous systems\n Background in robotics perception for drones or marine vehicles\n Experience with real-time embedded vision systems\n Familiarity with defense industry standards and security clearance processes\n Publications or contributions to computer vision research or open-source projects\n US Salary Range\n $166,000 — $220,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sop","salary_min":166000,"salary_max":220000,"location":"Costa Mesa, CA","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["robotics","cloud","computer-graphics","payments","computer-vision"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5145529007?gh_jid=5145529007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T18:28:05Z","expires_at":"2026-06-29T14:06:40.774659Z","created_at":"2026-05-27T14:07:00.648527Z","updated_at":"2026-05-30T14:06:40.886351Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/731f6d0a-ba12-48e0-98c0-e09482be412c"},{"id":"0344954d-9c09-460a-8b59-35f17075a617","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Software Engineer II, Lab Software","slug":"software-engineer-ii-lab-software-9b54dc8d","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking a Software Engineer II with backend experience to join our Lab Software Team (LaS), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.\n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 2-5 years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields.\n Lab Automation Experience: Experience with laboratory devices, robotics, or hardware drivers.\n Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions)\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $120,000 — $180,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. 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