{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n This role follows a hybrid work schedule and reports to a Software Tech Lead Manager.\n You will: \n \n \n Own and drive the roadmap for ML-powered pickup and dropoff features, from problem definition through launch, in partnership with PM, UX, data science, and other commercialization engineering teams\n \n Train, evaluate, and deploy ML models for occupancy detection, rider-vehicle interactions, pullover selection, and lost and found\n \n Design fallback systems that cascade between onboard and offboard models based on latency, confidence, and connectivity\n \n Build distributed systems that span vehicles, cloud services, and rider apps, and that handle intermittent and inconsistent connectivity well\n \n Work across the stack (data pipelines, model serving, backend services, and client integration) to ship end-to-end, user-facing features\n \n Define success metrics and use offline evaluation, simulation, and live experiments to measure impact on service quality and rider experience\n \n You have: \n \n \n BS degree in Computer Science or equivalent practical experience\n \n 5+ years of software engineering experience, including building and deploying ML models into production\n \n Experience building backend distributed systems\n \n We prefer: \n \n \n Experience with C++\n \n MS in Computer Science, or equivalent practical experience\n \n Experience in developing machine learning models, infrastructure, and pipelines\n \n Experience deploying models on-device or on edge hardware with compute and latency constraints\n \n Track record of owning ambiguous, user-facing problems end-to-end and setting your own technical direction\n \n Experience in autonomous vehicles or robotics\n \n Disclosure for WA Based \u0026 Remote Roles: \n In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:\n Health, dental, vision, life, disability insuranceRetirement Benefits: 401(k) with company matchPaid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employmentSick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year\n US Remote Only: Please note that Waymo may not be able to employ remotely in all US locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.\n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $213,000 — $263,000 USD","salary_min":213000,"salary_max":263000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["mlops","distributed-systems","data-pipeline","autonomous-vehicles","robotics","machine-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8212440","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T13:20:32Z","expires_at":"2026-11-13T16:55:54.938681Z","created_at":"2026-10-14T15:20:04.385328Z","updated_at":"2026-10-14T16:55:54.941384Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fcb2f68d-9ea2-439d-9d09-29431b4bdeec"},{"id":"7a65d567-bcff-488f-a593-6e31f5da1a79","company_id":"e939609d-98b9-49ee-9737-a7134cd10d11","title":"Deployment Engineer","slug":"deployment-engineer-f8b717e9","description":"About Comet \n Comet is building the development platform for teams who want to ship robust, reliable, and responsible AI applications. Opik, our open source LLM evaluation framework, has quickly become one of the most popular tools in the space. Our experiment management platform is used by data scientists at companies like Uber, Netflix, and Etsy. Tens of thousands of researchers, engineers, academics, and hobbyists use Comet every day to build the future of AI. \n Working at Comet will give you access to the most exciting work being done in all areas of machine learning. Some of the top researchers and companies working on self-driving cars, drug discovery, particle research, diffusion models, and LLMs use Comet every day. Your work has the potential to accelerate the development of some of the most impactful technology in the world, and you will be doing it alongside a team of passionate, caring individuals. If that sounds exciting, Comet is the right place for you.\n Comet is backed by more than $63 million in venture capital funding and powers some of the best machine-learning teams in the world, including Netflix, Uber, Etsy, and Mobileye. We are a remote-first company with offices in New York City (USA) and Tel Aviv (Israel).\n About the Role: \n Comet is looking for an experienced Deployment Engineer (located in the East or Central USA Only) to help our customers successfully deploy, operate, and troubleshoot Comet in their environments.\n This is a highly customer-facing engineering role . You will work directly with customers to understand their infrastructure and deployment requirements, lead deployments, troubleshoot complex issues, and drive problems through to resolution.\n You will also contribute to the engineering and automation behind our deployment solutions, including Kubernetes, Helm, Terraform, cloud infrastructure, tooling, and documentation.\n What You’ll Do: \n \n Work directly with customers to understand their infrastructure and deployment requirements.\n Deploy and maintain Comet across Kubernetes and cloud environments.\n Troubleshoot complex infrastructure and deployment issues across Kubernetes, networking, cloud services, databases, and application configuration.\n Own customer issues from investigation through resolution, collaborating with Engineering, Support, Customer Success, and other teams when needed.\n Develop and improve Helm charts, Terraform, deployment tooling, automation, and documentation.\n Participate in technical customer calls and explain complex topics clearly.\n Use AI tools for troubleshooting, development, automation, and investigation while validating results and maintaining engineering judgment.\n \n What We’re Looking For: \n \n Proven customer-facing technical experience is essential. \n Proven experience using AI tools in real engineering workflows, with the ability to critically evaluate and validate their output.\n Strong hands-on experience with  Kubernetes, Helm and containerized applications.\n Production experience with cloud infrastructure, preferably  AWS .\n Experience with  Infrastructure as Code , preferably Terraform.\n Strong Linux, networking, and infrastructure troubleshooting skills.\n Experience troubleshooting production systems using logs, metrics, and monitoring/observability tools.\n Excellent written and verbal communication skills.\n \n How you work:\n \n You take ownership and proactively move problems forward.\n You are passionate about troubleshooting unfamiliar systems and looking for root causes rather than quick workarounds.\n You can work independently while knowing when to collaborate or ask for help.\n You communicate progress, blockers, and decisions clearly - especially in a remote environment.\n You are comfortable with ambiguity and changing priorities.\n You work well across teams and care about both the customer experience and engineering quality.\n \n Nice to Have: \n \n Enterprise or self-hosted software experience.\n Multi-cloud or on-premises deployment experience.\n CI/CD and GitOps experience.\n MLOps or AI infrastructure experience.\n Software development experience.\n Startup experience.\n \n What We Offer: \n \n Competitive base salary - $150K-200K based on proven experience, skills and location.\n Competitive benefits package.\n Flexible working hours and remote work options.\n Opportunities for professional growth and development.\n A collaborative and innovative work environment.\n The chance to work with cutting-edge technologies and projects.\n This role will be fully remote , located in the East or Central USA Only , working with a global team (large presence in the US, Europe and Tel Aviv) – some flexibility with work hours is required.\n \n  \n Please note: We do not accept unsolicited resumes or candidate submissions from recruitment agencies for this position. \n  \n  \n Comet is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees without regard to race, religion, ","salary_min":150000,"salary_max":200000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["mlops","llm","diffusion-models","cloud","autonomous-vehicles"],"apply_url":"https://www.comet.com/site/about-us/careers/job/?gh_jid=8017201003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T21:02:46Z","expires_at":"2026-11-13T16:59:35.153106Z","created_at":"2026-10-14T15:23:07.034809Z","updated_at":"2026-10-14T16:59:35.156267Z","company_name":"Comet ML","company_slug":"comet-ml","company_logo_url":"https://www.google.com/s2/favicons?domain=comet.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7a65d567-bcff-488f-a593-6e31f5da1a79"},{"id":"208f6a9b-9968-46f0-aa68-f972d885cce0","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-fc07da4b","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198500,"location":"Boston, MA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","robotics","mlops","deep-learning","data-pipeline","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=8016984003#/8016984003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T17:27:51Z","expires_at":"2026-11-13T16:56:23.376677Z","created_at":"2026-10-14T15:20:30.457065Z","updated_at":"2026-10-14T16:56:23.379931Z","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/208f6a9b-9968-46f0-aa68-f972d885cce0"},{"id":"5d06e771-bce8-47ec-ab25-c7a09a6ec39e","company_id":"545e1785-0a1e-478e-b21c-cb7ffa7e0b88","title":"Senior Machine Learning Engineer, Vehicle Perception","slug":"senior-machine-learning-engineer-vehicle-perception-6d396019","description":"Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.\n\nOur work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud \u0026 AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.\n\n\nTEAM\nThe Vehicle Perception team at Woven by Toyota tackles the core challenges of machine learning for 3D perception, sensor fusion, and computer vision in autonomous vehicles. Our work involves a variety of challenges, such as analyzing petabytes of multimodal driving data, solving optimization problems in computer vision, minimizing latency on hardware accelerators, deploying scalable and efficient machine learning (ML) training and evaluation pipelines, and designing novel neural network architectures to advance state-of-the-art ML for onboard perception. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with human-centered automated driving solutions for personal and commercial applications.\nWHO ARE WE LOOKING FOR?\nThe team is looking for a skilled Machine Learning Engineer to help advance a cutting-edge machine learning system for perception foundation models leveraging large-scale multimodal sensor data. You will have the chance to design and implement innovative machine learning models for our next-generation autonomous vehicle platform, influencing millions of Toyota production vehicles. We are looking for individuals who are passionate about self-driving car technology and its potential impact on humanity. Furthermore, we highly value candidates who exhibit a \"giver\" mindset, consistently seeking opportunities to assist their colleagues while maintaining a strong focus on delivering solutions to production.\n","salary_min":140000,"salary_max":230000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","deep-learning","autonomous-vehicles","computer-vision","machine-learning"],"apply_url":"https://jobs.lever.co/woven-by-toyota/68d72c7e-e867-45e8-b81b-3315889bea75/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-07T16:35:57.897Z","expires_at":"2026-11-13T17:00:18.00542Z","created_at":"2026-10-14T15:23:51.750868Z","updated_at":"2026-10-14T17:00:18.008985Z","company_name":"Woven by Toyota","company_slug":"woven-toyota","company_logo_url":"https://www.google.com/s2/favicons?domain=woven.toyota\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5d06e771-bce8-47ec-ab25-c7a09a6ec39e"},{"id":"db835cf3-0130-489a-9931-b9d8c638a18d","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Engineer - Perception Modeling","slug":"senior-engineer-perception-modeling-3f6335e2","description":"On our Perception team, you have the opportunity to work with world-class ML engineers and research scientists, whose mission is to make self-driving vehicles a reality and to create a positive social impact. Our team works on the tech stack responsible for perceiving the dynamic scenarios, and further tracking and classifying objects around our robo-taxi. We are looking for engineers who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.\n What You'll Be Doing: \n \n Lead the architecture and development of advanced perception systems, focusing on, large-scale multi-modal foundation models, and robust knowledge generalization across vehicle generations\n Architect and scale synthetic data generation and sensor simulation capabilities to tackle long-tail edge cases, unseen off-log scenarios, and closed-loop evaluation\n Drive knowledge transfer from large teacher/foundation models to efficient onboard real-time perception models via advanced distillation and post-training techniques\n Productionize and deploy solutions onto autonomous vehicle fleets\n Provide technical leadership, mentorship, and guidance to senior and mid-level engineers on the team\n \n What We're Looking For: \n \n 3+ years of experience in Machine Learning, Computer Science, Robotics, or a related field\n Masters or Ph.D. in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience\n In-depth understanding of common Machine Learning and Deep Learning algorithms\n Experience with designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, multi-object tracking, and/or end-to-end perception\n Experience with deep learning frameworks such as TensorFlow or PyTorch\n Fluency in Python, including standard scientific computing libraries and Python bindings development experience\n Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods\n Excellent communication and interpersonal skills\n Experience mentoring and leading others\n \n Preferred, but not required: \n \n Proven track record in designing, training, or fine-tuning Foundation Models (e.g., Vision-Language Models, Multimodal Transformers) for autonomous driving or robotic perception\n Deep expertise in World Models, generative video/lidar prediction, scene synthesis, and sensor simulation for closed-loop evaluation\n Strong experience with Knowledge Distillation and model compression techniques to transfer capability from large offline teacher models to lightweight edge deployments\n Demonstrated experience with Synthetic Data Generation (SDG) and multi-modal automated labeling systems to scale training data quality and volume\n Publications in premier computer vision or machine learning conferences (e.g., CVPR, ICML, NeurIPS, ICCV, ECCV)\n \n  \n #LI-BP1 \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\n $172,000 — $229,000 USD \n Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more. \n Our journey is always people first. \n We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.\n Higher purpose, greater impact. \n We’re creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world diffe","salary_min":172000,"salary_max":229000,"location":"Boston, MA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["generative-ai","autonomous-vehicles","computer-vision","deep-learning","fine-tuning","robotics","pytorch","tensorflow"],"apply_url":"https://motional.com/open-positions/?gh_jid=8008804003#/8008804003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-06T17:15:40Z","expires_at":"2026-11-13T16:56:23.389669Z","created_at":"2026-10-14T15:20:30.46965Z","updated_at":"2026-10-14T16:56:23.392751Z","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/db835cf3-0130-489a-9931-b9d8c638a18d"},{"id":"389d3ac4-8c7f-4b52-810b-b05aeea8f4a8","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Senior, ML Engineer - Tracking","slug":"senior-ml-engineer-tracking-7090ab8b","description":"About the Company   \n At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. \n A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. \n Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.   \n Meet the Team \n Accurate and highly available information about other actors and objects is fundamental to the safe operation of autonomous trucks. Core capabilities depend on accurate tracking estimates to ensure safe and efficient vehicle behavior. \n The Tracking Team develops the ML models, state estimation algorithms, and production software responsible for associating and estimating the kinematics of other actors and objects in real time. Our solutions fuse information from multiple sensors and maintain robust performance despite sensor imperfections, environmental challenges, and system degradation. As part of this team, you will develop and deploy production-ready tracking solutions and help solve the challenges of bringing autonomous vehicle technology to real-world commercial applications. \n What You'll Do  \n \n Design, develop, and deploy production ML models for mulit-object tracking, including association, learned pose and kinematic estimation, and sensor fusion using camera, LiDAR, radar, and other vehicle sensors.   \n \n \n Develop scalable training and evaluation workflows using PyTorch, distributed training infrastructure, and large-scale real-world datasets.   \n \n \n Design and improve tracking and sensor fusion algorithms for robust vehicle pose and kinematics   \n \n \n Analyze large-scale vehicle data to characterize performance, identify failure modes, and drive model and system improvements.   \n \n \n Develop robust, efficient production software in modern C++ and Python across the full development lifecycle.   \n \n \n Define evaluation, verification, and validation strategies to ensure Tracking quality, robustness, and safety across diverse operating conditions.   \n \n \n Make technical design and architecture decisions, balancing model performance, computational efficiency, robustness, and production constraints.   \n \n \n Collaborate with perception, mapping, planning, controls, and platform teams to deliver integrated autonomous driving capabilities.   \n \n \n Provide technical leadership through design reviews, code reviews, mentoring, and development of engineering best practices.   \n \n   What You'll Need to Succeed  \n \n Bachelor’s degree in Computer Science, Software Engineering, Robotics, or a related field with 6+ years of relevant industry experience, or a Master’s degree with 3+ years of relevant industry experience, or a PhD with 1+ year of relevant industry experience.   \n \n \n Experience with AV or robotics perception systems (tracking, detection, SLAM, scene modeling, ect.).   \n \n \n Strong experience developing and deploying ML models for perception, localization, or sensor fusion domains.    \n \n \n Proficiency with PyTorch and modern ML tooling for training, inference, and optimization.    \n \n \n Solid understanding of 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals.    \n \n \n Demonstrated ability to work with large multimodal datasets and build scalable pipelines for processing, labeling, and evaluation.   \n \n \n Strong software engineering fundamentals in Python and C++, including algorithms, data structures, testing, debugging, and performance optimization.   \n \n \n Strong written and verbal communication skills and the ability to work effectively on cross-functional teams.   \n \n   Bonus Points  \n \n Experience with state estimation techniques such as factor graphs, Kalman filtering, nonlinear optimization, or related probabilistic estimation methods.   \n \n \n Familiarity with distributed computing tools such as Ray, Kubernetes, or similar orchestration frameworks.    \n \n \n Knowledge of embedded and real-time constraints for on-vehicle deployment.    \n \n \n Experience in simulation, synthetic data generation, and uncertainty-aware ML modeling.    \n \n \n Contributions to open-source robotics, perception, or ML frameworks.    \n Familiarity with functional safety standards and automotive development processes, including ISO 26262.   \n \n  \n Perks of Being a Full-time Torc’r \n Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:    \n \n A competitive compensation package that includes a bonus component and stock options   \n \n \n 100% paid medical, ","salary_min":177300,"salary_max":212800,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","autonomous-vehicles","pytorch","robotics","payments","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8765541002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-06T13:58:16Z","expires_at":"2026-11-13T16:56:17.79822Z","created_at":"2026-10-14T15:20:25.98843Z","updated_at":"2026-10-14T16:56:17.801031Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/389d3ac4-8c7f-4b52-810b-b05aeea8f4a8"},{"id":"ec278267-477d-4688-a758-54877ad70f37","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Machine Learning Engineer II - Learned Planning (Reinforcement Learning)","slug":"machine-learning-engineer-ii-learned-planning-reinforcement-learning-6785c795","description":"About the Company  \n At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. \n A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. \n Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. \n Meet the Team:   As a Machine Learning Engineer II – Learned Behaviors, you will help develop and deploy  behavior models that power decision-making for autonomous trucks. Working closely with teams across perception, prediction, planning, and safety, you will contribute to learned behavior modules that enable safe, efficient, and human-like driving in real-world freight operations.    This role focuses on building, validating, and improving machine learning models and infrastructure that support learned behavior systems within the autonomy stack.    What You’ll Do  \n \n Develop and train machine learning models for learned behavior systems, including approaches such as behavior cloning, imitation learning, and reinforcement learning.\n Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack.\n Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across scenarios.\n Contribute to model training pipelines and data workflows, curating behavior datasets from simulation, fleet logs, and on-vehicle data.\n Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across diverse driving environments.\n Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.\n Support the development of tooling and infrastructure that improves experimentation speed, reproducibility, and model iteration.\n Contribute to technical discussions around model architecture and training strategies within the team. \n \n What You’ll Need to Succeed  \n \n Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of industry experience, or a Master’s degree with 2+ years of experience. \n Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments.\n Strong programming skills in Python and PyTorch, with experience writing production-quality ML code.\n Experience training and evaluating machine learning models using large datasets and scalable compute environments.\n Understanding of ML architectures used in autonomy systems, such as transformers, graph neural networks, or sequence models.\n Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines.\n Ability to collaborate with cross-functional teams to integrate ML models into larger software systems. \n \n Bonus Points!  \n \n Experience working in autonomous driving, robotics, or simulation-based training environments.\n Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray).\n Experience working with simulation environments or large-scale behavior datasets.\n Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems.\n Experience deploying ML models into production or real-world robotics systems. \n \n Perks of Being a Full-time Torc’r   Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:     \n \n A competitive compensation package that includes a bonus component and stock options\n 100% paid medical, dental, and vision premiums for full-time employees\n 401K plan with a 6% employer match\n Flexibility in schedule and generous paid vacation (available immediately after start date)\n AD+D and Life Insurance \n \n At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.  Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. \n For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United S","salary_min":153200,"salary_max":183800,"location":"Ann Arbor, MI","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["deep-learning","distributed-systems","payments","reinforcement-learning","agents","autonomous-vehicles","pytorch","robotics"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8852888002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-29T21:15:57Z","expires_at":"2026-11-13T16:56:17.74727Z","created_at":"2026-10-14T15:20:25.93453Z","updated_at":"2026-10-14T16:56:17.749834Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ec278267-477d-4688-a758-54877ad70f37"},{"id":"35a26375-0260-4b78-9e21-8ad9674ad9cb","company_id":"545e1785-0a1e-478e-b21c-cb7ffa7e0b88","title":"Engineering Manager, ML Training Infrastructure","slug":"engineering-manager-ml-training-infrastructure-ee163ad0","description":"Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.\n\nOur work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud \u0026 AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.\n\n\nAbout the Team\nEnterprise AI is a platform that provides end-to-end machine learning tooling experience to support and accelerate machine learning development, including autonomous driving and other related projects. Our platform serves customers as a standardized machine learning platform within Woven by Toyota as the larger Toyota Group companies.\nThe Enterprise AI ML Training Infrastructure team builds and operates the infrastructure that enables engineers and researchers to train, evaluate, and iterate on machine learning models at scale. Our customers include teams working on AD/ADAS and Woven City, where large-scale machine learning workloads, simulation, and data processing are critical to developing the next generation of mobility technologies.\nThe team operates at the intersection of machine learning, distributed systems, cloud infrastructure, and developer platforms. Our systems include large-scale GPU compute environments, Kubernetes-based cluster infrastructure, and workflow and pipeline orchestration technologies such as Ray, Airflow, and Temporal.\nWe are looking for an Engineering Manager to lead a team to help shape the technical direction, engineering culture, and long-term evolution of our ML training infrastructure platform.\n \nWHO ARE WE LOOKING FOR?\nAs the Engineering Manager, ML Training Infrastructure, you will lead the team responsible for building and operating the infrastructure that powers machine learning training workloads across Woven by Toyota.\nYou will combine engineering leadership with strong technical judgment. You will work closely with engineering, research, and product stakeholders to understand customer needs, translate them into scalable technical solutions, and ensure that our platform is reliable, efficient, secure, and easy to use.\nThis role is particularly suited to an engineering leader who enjoys working on complex infrastructure problems and is comfortable operating across Kubernetes, distributed systems, GPU infrastructure, cloud platforms, and machine learning workloads.\nYou will also play an important role in building a strong engineering culture, developing engineers, establishing effective engineering practices, and partnering with our customers to continuously improve the platform.\n \nWhat You Will Enable\nIn this role, you will help build the infrastructure that enables teams across Woven by Toyota to train and operate increasingly large and sophisticated machine learning workloads.\nYour work will directly support engineers and researchers working on AD/ADAS, Woven City, and other mobility initiatives by making compute resources easier to access, workloads more reliable, and ML development faster and more scalable.\nYou will have the opportunity to shape both the technical architecture of a critical ML infrastructure platform and the engineering culture of the team building it.\n","salary_min":140000,"salary_max":260000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["gpu","distributed-systems","cloud","autonomous-vehicles","infrastructure"],"apply_url":"https://jobs.lever.co/woven-by-toyota/b7844018-80f2-4d52-9749-496cf50cb182/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-28T17:26:53.682Z","expires_at":"2026-11-13T17:00:17.974246Z","created_at":"2026-10-14T15:23:51.72398Z","updated_at":"2026-10-14T17:00:17.977194Z","company_name":"Woven by Toyota","company_slug":"woven-toyota","company_logo_url":"https://www.google.com/s2/favicons?domain=woven.toyota\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/35a26375-0260-4b78-9e21-8ad9674ad9cb"},{"id":"c0052234-bd6e-4ec1-847e-cf309c220c0b","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director of Data Science","slug":"director-of-data-science-a1930889","description":"Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, verifying and validating the autonomy stack, and defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis. \n Mission Summary: \n As the Director of Data Science, you will lead the strategic vision and execution for extracting intelligence from petabyte-scale on-road fleet data and simulation ecosystems. This leadership role is centered on building advanced data-driven methodologies, developing predictive and generative models, and serving as the primary analytical anchor supporting not only the Systems Readiness and Performance/Metrics teams but the whole company. You will drive the statistical rigor necessary to translate raw road data into high-fidelity performance metrics that directly inform vehicle launch readiness and safety-critical decisions. \n What You'll Be Doing: \n \n Rapid Operational Analytics: Execute fast-turnaround investigations on emergent fleet issues, converting real-time operational data into high-impact insights for launch decisions.\n Advanced Exposure Modeling: Build complex statistical models to evaluate vehicle safety and performance across diverse environmental variables and Operational Design Domains.\n Cross-Functional Partnership: Serve as the primary analytical anchor for Systems and Autonomy teams (Perception, Prediction, Planning).\n Executive Artifacts: Work with other systems teams to distill raw telemetry and rapid-response findings into high-level strategy documents, visualizations, and dashboards.\n Team Leadership: Mentor and scale a dedicated four-person team, instilling a culture that pairs rapid analytical agility with absolute scientific rigor. \n \n What We're Looking For: \n \n Industry Experience: 10+ years of professional experience leading data science or applied AI/ML initiatives, with at least 5 years explicitly scaling data-driven programs for autonomous driving, robotics, or complex safety-critical engineering systems.\n Educational Background: Master’s degree or PhD in Data Science, Computer Science, Robotics, Mathematics, Physics, or a highly quantitative field.\n Expertise in Advanced Analytics: Deep foundational knowledge in statistical analysis, density estimation, hypothesis testing, uncertainty quantification, and causal reasoning.\n Technical Proficiency: Mastery of Python, SQL, and data science infrastructure libraries, alongside a strong understanding of modern sequence modeling (Transformers) and distributed compute scaling frameworks (e.g., Ray, AWS).\n System Deconstruction: Demonstrated track record of translating ill-defined, ambiguous real-world performance questions into structured metric designs and concrete solution architectures.\n Exceptional Communication: Proven capacity to articulate highly technical data patterns and trade-offs into compelling strategies for cross-functional engineering peers and C-suite executives.\n Collaborative Leadership: Strong interpersonal ability to wield cross-functional technical influence, resolve technical disagreements across teams, and establish organizational best practices around data integrity. \n \n Bonus Points (not required): \n \n \n Experience designing reward functions or applying Inverse Reinforcement Learning (IRL) to evaluate human-like driving intent, assertiveness, and comfort.\n \n Familiarity with physical AI ecosystems, open-weights Vision-Language models (VLMs), or processing raw telemetry without text-translation bottlenecks.\n \n Direct experience evaluating core onboard software subsystems like Perception, Prediction, or Motion Planning.\n \n Deep familiarity with functional safety engineering standards like ISO 26262 and ISO 21448 (SOTIF)\n \n This is a unique opportunity to make a meaningful impact at Motional by enhancing our data understanding and accelerating development speed for our industry-leading autonomous vehicle metrics and capabilities ecosystem. We take pride in having some of the brightest and most dedicated talent in the world on our team. If you're innovative, driven, and eager to tackle challenges, we'd love to have you join us! \n Physical Demands: \n While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or ","salary_min":288000,"salary_max":396000,"location":"Boston, MA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","robotics","autonomous-vehicles","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=8005531003#/8005531003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-25T17:33:47Z","expires_at":"2026-11-13T16:56:23.308917Z","created_at":"2026-10-14T15:20:30.396025Z","updated_at":"2026-10-14T16:56:23.312167Z","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/c0052234-bd6e-4ec1-847e-cf309c220c0b"},{"id":"b34460f0-6838-4cce-be43-ee804be68816","company_id":"63839083-85dd-4aa0-b128-254fc82866e5","title":"Senior / Staff ML Ops Engineer","slug":"senior-staff-ml-ops-engineer-e5400509","description":"Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.\n \nWith offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai\n\n\nYou will..\nBuild and evolve our training infrastructure on Kubernetes with Infrastructure — GPU scheduling, autoscaling, multi-node distributed jobs, capacity strategy, and the operators and workflow engines that keep long-running training reliable.\nShape the developer-facing surface — CLIs, SDKs, job submission, templates, paved paths — designed with the teams who'll use them. Make the common case one command and keep the uncommon case possible.\nShorten the inner loop. Time to first training run, edit-to-signal latency, local iteration before a job hits the cluster, fast failure over slow mystery. Measure it, publish it, drive it down.\nEvangelize best-in-class tooling and frameworks. Track what the ecosystem is shipping, evaluate honestly, and make the case with working prototypes and migration paths — or say plainly when a shiny thing isn't worth the switching cost.\nStrengthen the data and artifact layer. Dataset versioning, sharding, and high-throughput loading of large multimodal sensor data, so jobs saturate GPUs instead of waiting on I/O.\nTurn one-off Python into durable tooling — tested, documented, observable libraries, CLIs, and services with sane defaults, and deletions where they're overdue.\nMake experiments legible, with the teams who live in them: experiment hygiene, dashboards researchers trust, a real model registry, and lineage from dataset to checkpoint to simulation result.\nShip CI/CD for models alongside autonomy and simulation, so a model change is validated the same way a code change is.\nBuild observability across the ML stack — utilization, throughput, failure modes, queue times, cost per experiment. When a job fails at 3am on node 47, the researcher should find out why without you.\nTreat docs, onboarding, and support as product surface — golden-path guides, a new researcher productive on day two, office hours that turn repeat questions into shipped fixes.\nDrive adoption, not just availability. Prototype with real users, watch them work, iterate. A tool nobody adopts didn't ship.\nMake the platform boringly reliable — fewer failures, faster recovery, and none of the manual steps that quietly cost a team days.\nBuild guardrails that don't feel like walls, with Security, IT, and Infrastructure: access controls, data handling, and cost governance that hold up in an IP-sensitive environment while staying self-serve.\n \nQualifications:\n5+ years of software or infrastructure engineering, including tools or platforms used by other engineers and operating ML or data-intensive production systems.\nHands-on Kubernetes expertise — GPU scheduling, autoscaling, Helm or equivalent, networking fundamentals, and the ability to debug a cluster under load rather than restart it.\nExcellent Python, and a track record of designing APIs and CLIs other people enjoy using.\nPractical AWS depth: object storage at scale, IAM, GPU compute, networking, cost management, and infrastructure as code (Terraform, Pulumi, or similar).\nDistributed training in PyTorch (DDP, FSDP, or similar), plus experiment tracking and model registry tooling — from the perspective of someone who made them pleasant for others to use.\nFluency with containers, CI/CD, and modern build systems, including large monorepos.\nThe ability to influence without authority: evaluate a framework on its merits, pilot it credibly, and persuade skeptical senior engineers to change how they work.\nA collaborative default — you'd rather co-own a system than draw a boundary around your part of it.\nUser empathy: you'd rather fix the third-most-interesting problem blocking ten people than the most interesting one blocking nobody.\nStrong product instincts, strong writing, and comfort operating autonomously in ambiguous territory.\nPassionate about self-driving technologies and frontier AI, and about what a small, world-class team can do with the right infrastructure.\n \nBonus/nice to have: \nInternal developer platform, research platform, or DevEx work — with a story about a tool whose adoption you grew from zero.\nLarge-scale distributed GPU training: hundreds to thousands of accelerators, NCCL, high-performance cluster networking, collective communication tuning.\nHigh-throughput loading of LiDAR or camera data, and formats such as Parquet or WebDataset.\nWorkflow and scheduling systems — Argo Workflows, Ray, Flyte, Kubeflow, or Slurm.\nBuild-system depth (Bazel or similar), inclu","salary_min":184000,"salary_max":272000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["pytorch","autonomous-vehicles","robotics","data-pipeline","cloud","mlops","distributed-systems"],"apply_url":"https://jobs.lever.co/waabi/1c01bf84-38e3-42db-990c-29c9195443ba/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-23T23:09:15.023Z","expires_at":"2026-11-13T16:56:19.803645Z","created_at":"2026-10-14T15:20:27.445903Z","updated_at":"2026-10-14T16:56:19.806943Z","company_name":"Waabi","company_slug":"waabi","company_logo_url":"https://www.google.com/s2/favicons?domain=waabi.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b34460f0-6838-4cce-be43-ee804be68816"},{"id":"a1fdf581-2cfe-43eb-b7db-c5e4a939cffc","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Staff Tech Lead, ML Data Infrastructure and Inference Platform ","slug":"staff-tech-lead-ml-data-infrastructure-and-inference-platform-704ea4cd","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 ML Data Infrastructure and Inference Platform team owns the Data as well as the Data infrastructure for all ML Flywheels at Waymo. We do this via a planet scale centralized feature store for all  ML training and evaluation, the feature extraction framework as well the inference platform for generating the data via bulk and online inferences. The objective of the team is to deliver data necessary for all our onboard as well Foundation Models to make the ML Flywheel successful and in turn lead to the successful scaling of Waymo.  The team is highly collaborative and closely works with all modeling teams within Waymo.\n You will: \n \n As a Tech Lead you’ll  build, lead and contribute to Waymo’s ML data infrastructure platform to enable planet scale ML Flywheel for all ML models at Waymo via data store and data infra ecosystem.\n Work closely with teams across Waymo both onboard \u0026 offboard Foundation models, to understand the data infra needs, data distributions, data quality, data value, freshness and onboard these flywheels onto our planet scale data store and ensure the seamless adoption and guide the development of our infra components. \n You will closely lead, mentor and guide a team of engineers to build and onboard teams to the infrastructure efficiently.\n The team has a large surface area and scope in terms of impact, cross team collaboration and direct interaction with ML models at Waymo. \n \n You have: \n \n 6+ years of professional experience in the field of software engineering\n Experience tech leading projects with high cross team collaboration \n Experience tech leading a team of engineers on complex projects\n Experience in programming C++ \n Experience with building highly scalable distributed system\n Experience with ML Data and ML Flywheels\n \n We prefer: \n \n Passionate about Data and building ML infra \u0026 tools\n Experience Tech leading projects, cross functional projects\n Experience with handling large datasets in the order of exabytes\n Experience building machine learning infrastructure  and model hosting / inference infrastructure\n Experience with production services with high QPS.\n \n #LI-Hybrid\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","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","distributed-systems","generative-ai","infrastructure","inference"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8142863","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-23T16:38:41Z","expires_at":"2026-11-13T16:55:55.288456Z","created_at":"2026-10-14T15:20:04.745628Z","updated_at":"2026-10-14T16:55:55.291576Z","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/a1fdf581-2cfe-43eb-b7db-c5e4a939cffc"},{"id":"2424c1ce-b300-4939-8187-d3ededb9970b","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Research Scientist, World Model Post-Training","slug":"research-scientist-world-model-post-training-504a059c","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 mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.\n In this hybrid role, you will report to a Software Engineering Manager.\n You will: \n \n Conduct applied world model research and development\n Post-train Waymo’s world model\n Design compelling experiments by training and evaluating large generative models\n Present results to peers and leadership\n Leverage AI to write high quality code, unit tests, and documentation, and automate workflows\n \n You have: \n \n Masters or PhD in deep learning in generative / world modeling\n 3+ years of experience with modern deep learning frameworks (e.g., JAX, TensorFlow 2, Pytorch)\n Experience with diffusion / flow matching models\n Experience with reinforcement learning\n Experience training large foundational models\n \n We prefer: \n \n Experience with post-training of foundational models\n Experience with reinforcement learning for diffusion / flow matching models\n Experience with distillation\n Experience with autonomous vehicles\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 $213,000 — $263,000 USD","salary_min":213000,"salary_max":263000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["reinforcement-learning","pytorch","autonomous-vehicles","deep-learning","tensorflow","research"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8222098","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-22T16:48:50Z","expires_at":"2026-11-13T16:55:54.995986Z","created_at":"2026-10-14T15:20:04.436747Z","updated_at":"2026-10-14T16:55:54.998704Z","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/2424c1ce-b300-4939-8187-d3ededb9970b"},{"id":"283dcfc4-cab7-4cad-b1e5-73ca0cca74a1","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Manager, Simulation Infrastructure","slug":"manager-simulation-infrastructure-e17ab7a9","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 As the Manager of Simulation Infrastructure, you will lead a team of full-stack and infrastructure engineers responsible for the deployment, scaling, and operational health of the web applications, databases, and cloud infrastructure supporting massive parallel batch simulation runs. You will drive the strategic roadmap, guide the architectural design of secure, high-throughput APIs, and oversee the frontend-to-backend systems that power scenario management, run orchestration, and results analytics. Additionally, you will focus on building and developing a high-performing team, fostering a culture of engineering excellence, partnering with the Simulation Engine team to align on integration interfaces, and ensuring platform reliability, observability, and cost-efficiency.\n Essential Responsibilities \n \n Recruit, manage, and mentor a team of high-performing full-stack and infrastructure engineers, focusing on their career growth, performance, and overall team health.\n Own the strategic roadmap and execution for the web applications and tools that support simulation workflows (scenario management, run orchestration, tagging and taxonomy, and results analytics).\n Guide the architectural decisions for scalable cloud infrastructure and container orchestration designed to support massive, parallel batch simulation runs.\n Oversee the design and maintenance of relational databases and secure, high-throughput APIs that connect frontend portals to the underlying simulation systems.\n Drive engineering best practices, reliability, observability, and cost-efficiency across the platform.\n Partner closely with the Simulation Engine team and other stakeholders to align technical capabilities with business needs, define clean integration interfaces, and manage complex, multi-quarter projects.\n \n Skills and Abilities \n Success in this role typically requires the following competencies: \n \n Proven track record in engineering management and building healthy, high-performing technical teams.\n Deep understanding of container orchestration (e.g., Kubernetes) and architectural principles for cloud scalability, resilience, and operational health.\n Strong technical foundation in relational database design (schema design, performance tuning) and scalable backend web services (e.g., Go, Python, Node.js).\n Familiarity with modern frontend frameworks (e.g., React), plus a strong grasp of CI/CD, observability, and infrastructure-as-code methodologies.\n Exceptional communication and leadership skills, with the ability to bridge the gap between technical execution and high-level product strategy.\n \n Qualifications and Experience \n Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience: \n Required Qualifications: \n \n B.S., M.S. or Ph.D. Degree in Computer Science, Software Engineering, or a related technical field (or equivalent experience).\n 5+ years of software engineering experience spanning backend services and cloud infrastructure, including at least 2+ years of direct people management experience.\n Demonstrated experience guiding teams that operate production workloads on container orchestration platforms (e.g., Kubernetes) at scale, alongside strong relational database ecosystems (e.g., PostgreSQL).\n Solid foundational background in building secure, high-throughput APIs and web services (Go, Python, and/or Node.js) with modern frontends such as React.\n Proven experience recruiting, building, and mentoring full-stack or infrastructure engineering teams.\n \n Desirable Qualifications: \n \n Experience managing teams that support large-scale batch or parallel compute workloads.\n Track record of successfully managing cloud cost optimization and observability initiatives.\n Experience overseeing teams that utilize infrastructure-as-code and mature CI/CD pipelines.\n Experience overseeing the development of internal developer tools or self-service platforms for technical users.","salary_min":181280,"salary_max":263500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["robotics","cloud","autonomous-vehicles","healthcare","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8811975002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-22T15:09:33Z","expires_at":"2026-11-13T17:02:54.003619Z","created_at":"2026-10-14T15:24:57.018747Z","updated_at":"2026-10-14T17:02:54.006675Z","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/283dcfc4-cab7-4cad-b1e5-73ca0cca74a1"},{"id":"5d6b88d7-c242-45d2-aadd-f78f5daacd0a","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Senior, Machine Learning Engineer - Camera Model","slug":"senior-machine-learning-engineer-camera-model-3e7c2f1f","description":"About the Company   At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.     A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight.     Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.     Meet the Team   As a Senior Machine Learning Engineer – Camera Models, you will develop and deploy machine learning models that power camera-based perception for autonomous trucks. The Camera Models team builds and maintains core vision systems that enable the autonomy stack to understand the environment, detect and localize objects, and estimate scene structure from camera data.     Working closely with teams across perception, data, and infrastructure, you will own the development and improvement of robust, scalable camera-based models that support safe and reliable autonomous driving in real-world freight environments.   This role focuses on owning model development for scoped problem areas, improving system performance through iteration, and delivering production-ready machine learning solutions within the autonomy stack.     What You’ll Do   \n \n Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding) \n Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment\n Write production-quality ML code to support scalable training, evaluation, and inference pipelines\n Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization\n Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking\n Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases\n Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack\n Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration\n Contribute to model architecture decisions and technical discussions within the team\n Mentor junior engineers on implementation, debugging, and best practices   \n \n What You’ll Need to Succeed   \n \n Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience \n Experience developing and deploying deep learning models for computer vision or perception systems\n Strong programming skills in Python and PyTorch, with experience writing production-quality ML code\n Experience training and evaluating models using large-scale datasets and distributed compute environments\n Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, multi-task models)\n Experience debugging model behavior, analyzing performance metrics, and improving model reliability\n Ability to translate ambiguous problems into structured ML solutions and deliver independently\n Experience collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems   \n \n   Bonus Points:   \n \n Experience in autonomous driving, robotics, or simulation-based ML systems \n Experience with multi-task learning or unified perception architectures\n Experience with large-scale data pipelines, distributed training systems (e.g., Ray), or experiment management frameworks\n Familiarity with camera calibration, geometric reasoning, or 3D perception from images (e.g., BEV, monocular depth, structure-from-motion)\n Experience deploying ML models into production or real-world robotics systems   \n \n Work Location: For this position, we are open to hiring in Montreal, Canada or remote within Canada  \n Perks of Being a Full-time Torc’r (Canada) Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:\n \n A competitive compensation package that includes a bonus component and stock options\n Medical, dental, and vision for full-time employees\n RRSP plan with a 6% employer match\n Public Transit Subsidy (Montreal area only)\n Flexibility in schedule and generous paid vacation\n Company-wide holiday office closures\n Life Insurance\n \n  \n At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discrim","salary_min":168000,"salary_max":193000,"location":"Montreal, Canada","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["computer-vision","robotics","payments","autonomous-vehicles","distributed-systems","deep-learning","pytorch","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8827921002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-21T20:37:00Z","expires_at":"2026-11-13T16:56:17.775333Z","created_at":"2026-10-14T15:20:25.966408Z","updated_at":"2026-10-14T16:56:17.777969Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5d6b88d7-c242-45d2-aadd-f78f5daacd0a"},{"id":"e87f9887-3562-48a8-bf92-fed27a6dbde0","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Senior, Machine Learning Engineer - Camera Model","slug":"senior-machine-learning-engineer-camera-model-47221bf5","description":"About the Company   At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.     A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.  Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight.     Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.     Meet the Team  \n As a Senior Machine Learning Engineer – Camera Models, you will develop and deploy machine learning models that power camera-based perception for autonomous trucks. The Camera Models team builds and maintains core vision systems that enable the autonomy stack to understand the environment, detect and localize objects, and estimate scene structure from camera data.     Working closely with teams across perception, data, and infrastructure, you will own the development and improvement of robust, scalable camera-based models that support safe and reliable autonomous driving in real-world freight environments.   This role focuses on owning model development for scoped problem areas, improving system performance through iteration, and delivering production-ready machine learning solutions within the autonomy stack.     What You’ll Do   \n \n Design, develop, and deploy deep learning models for camera-based perception (e.g., object detection, segmentation, depth estimation, scene understanding) \n Own end-to-end model development for scoped areas, from data curation and training to evaluation and deployment\n Write production-quality ML code to support scalable training, evaluation, and inference pipelines\n Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization\n Contribute to and improve large-scale training pipelines, including dataset preparation, distributed training, and experiment tracking\n Partner with data teams to improve dataset quality, including labeling strategies and coverage of edge cases\n Collaborate with perception, simulation, and validation teams to evaluate and integrate models into the autonomy stack\n Improve tooling, workflows, and infrastructure to accelerate experimentation and model iteration\n Contribute to model architecture decisions and technical discussions within the team\n Mentor junior engineers on implementation, debugging, and best practices   \n \n What You’ll Need to Succeed   \n \n Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master’s degree with 3+ years OR PhD with 1+ years of experience \n Experience developing and deploying deep learning models for computer vision or perception systems\n Strong programming skills in Python and PyTorch, with experience writing production-quality ML code\n Experience training and evaluating models using large-scale datasets and distributed compute environments\n Solid understanding of modern deep learning architectures used in perception (e.g., CNNs, transformers, multi-task models)\n Experience debugging model behavior, analyzing performance metrics, and improving model reliability\n Ability to translate ambiguous problems into structured ML solutions and deliver independently\n Experience collaborating cross-functionally to integrate ML models into larger autonomy or robotics systems   \n \n Bonus Points:   \n \n Experience in autonomous driving, robotics, or simulation-based ML systems \n Experience with multi-task learning or unified perception architectures\n Experience with large-scale data pipelines, distributed training systems (e.g., Ray), or experiment management frameworks\n Familiarity with camera calibration, geometric reasoning, or 3D perception from images (e.g., BEV, monocular depth, structure-from-motion)\n Experience deploying ML models into production or real-world robotics systems   \n \n Work Location: For this position, we are open to hiring in either the Ann Arbor, MI OR Blacksburg, VA (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States     Perks of Being a Full-time Torc’r   Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers: \n \n A competitive compensation package that includes a bonus component and stock options \n 100% paid medical, dental, and vision premiums for full-time employees\n 401K plan with a 6% employer match\n Flexibility in schedule and generous paid vacation (available immediately after start date)\n Company-wide holiday office closures\n AD+D and Life Insurance     \n \n   At","salary_min":177300,"salary_max":212800,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","robotics","computer-vision","distributed-systems","payments","data-pipeline","pytorch","deep-learning"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8765533002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-21T19:02:09Z","expires_at":"2026-11-13T16:56:17.770196Z","created_at":"2026-10-14T15:20:25.96197Z","updated_at":"2026-10-14T16:56:17.773855Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e87f9887-3562-48a8-bf92-fed27a6dbde0"},{"id":"d438b241-dc16-41f3-8ce3-782eb7b8e1cb","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Senior Software Performance Engineer","slug":"senior-software-performance-engineer-a23c7591","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 As a Senior Performance Engineer on the Behavior Planning team, you will own latency, throughput, memory utilization, and thread safety for our real-time decision-making pipeline. Working alongside staff roboticists who write high-level autonomy logic, your job is to profile the stack, enforce performance budgets, and build execution guardrails that guarantee deterministic, high-throughput execution.\n Prior background in autonomous vehicles, controls, or robotics math is not required . We are seeking engineers obsessed with system performance, low-level execution concepts, and software profiling tools. \n Essential Responsibilities \n \n System Diagnostics: Instrument the behavior pipeline to measure runtime performance, isolating latency spikes, resource contention, and memory inefficiencies.\n Pipeline Optimization: Refactor high-frequency execution loops to maximize cache utilization, eliminate dynamic memory allocations, and reduce tail latency.\n Concurrency Architecture: Re-engineer thread boundaries and synchronization logic to maximize multi-core parallel processing while ensuring thread safety.\n Performance Guardrails: Build automated micro-benchmarks and runtime telemetry into CI/CD pipelines to prevent algorithm developers from introducing performance regressions.\n API Design: Partner with autonomy teams to establish performant, low-overhead C++ module interfaces for new behavioral features.\n \n Required Qualifications \n \n Systems \u0026 Hardware Knowledge: Deep understanding of CPU cache hierarchies (L1/L2/L3), memory alignment, lock-free concurrency models, and Linux OS thread scheduling.\n Profiling \u0026 Diagnostic Tooling: Hands-on experience with Linux profiling toolchains (e.g., Perf, Tracy, eBPF) and dynamic sanitizers (ASan, TSan, Valgrind).\n C++ Engineering: Strong proficiency in modern C++ (C++17/20) with a focus on writing low-overhead abstractions, RAII, and cache-friendly data layouts.\n Benchmarking Methodologies: Familiarity with micro-benchmarking frameworks (e.g., Google Benchmark) and performance-regression testing in continuous integration.\n Domain Background: Experience in performance-critical software environments such as game engines, financial technology, database runtimes, or operating system kernels.\n Degree Requirement: B.S. Degree in Computer Science, Computer Engineering, or an equivalent degree.\n \n Desirable Qualifications \n \n Academic Advancement: Master’s degree or PhD in Computer Science, Computer Engineering, or a related field.\n Professional Depth: At least 5 years of professional experience.\n Domain Expertise: Prior experience in AV, robotics, or high-throughput real-time control systems.\n Advanced Process Ownership: Proven track record of designing and scaling automated CI/CD performance testing infrastructure.\n \n \n \n \n \n \n \n \n Benefits and Perks \n \n Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. \n Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.\n Rich retirement benefits, including an immediately vested employer safe harbor match.\n Generous paid parental leave as well as a phased return to work. \n Flexible vacation policy in addition to paid company holidays.\n Total Wellness Program providing numerous resources for overall wellbeing   \n \n Don’t meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we’re committed to building a diverse, inclusive, and authentic workforce, so if you’re excited about this role but your previous experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May.\n Want to learn more about our culture \u0026 benefits? Check out our  website ! ","salary_min":160000,"salary_max":180000,"location":"Ann Arbor, MI","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","robotics","api-design","healthcare"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8769365002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-21T15:16:47Z","expires_at":"2026-11-13T17:02:54.048887Z","created_at":"2026-10-14T15:24:57.062827Z","updated_at":"2026-10-14T17:02:54.051976Z","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/d438b241-dc16-41f3-8ce3-782eb7b8e1cb"},{"id":"59be4066-7b6b-4296-aa3e-fdd01c2e1ff6","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Machine Learning Engineer, Driver Refinement \u0026 Validation, Perception","slug":"machine-learning-engineer-driver-refinement-validation-perception-e0c4f50c","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 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 Our goal is to improve the Waymo Driver performance by owning the end-to-end driving behavior for various onroad problems clusters. We work with upstream and the downstream teams on developing the ML models and integrating into the Waymo Driver. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.\n In this hybrid role, you will report to a Technical Lead Manager.\n You will: \n \n Own tasks in the ML Driver, take responsibility for task performance, create ML methods and recipes to scale and improve tasks.\n Analyze behavior of ML systems in real-world application, identify issues and root causes, advise or develop short- and long-term solutions.\n Develop methods and recipes for distributed fine-tuning enabling multiple developers to simultaneously improve the model, develop methods and recipes to avoid regression against a production system.\n Monitor ML systems in production, develop methods for automatically detecting issues or regressions, develop AI-aided analysis and debugging tooling.\n Develop and maintain model evaluation recipes and metrics for measuring and improving performance of pre-trained and fine-tuned models\n \n You have: \n \n Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience\n 3+ years experience in Machine Learning and/or Computer Vision\n Experience with Python or C++\n Experience with ML frameworks like PyTorch or JAX\n \n We prefer: \n \n MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline\n Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI\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":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["robotics","autonomous-vehicles","fine-tuning","deep-learning","pytorch","computer-vision","machine-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8212478","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-18T17:08:17Z","expires_at":"2026-11-13T16:55:54.933929Z","created_at":"2026-10-14T15:20:04.381051Z","updated_at":"2026-10-14T16:55:54.93728Z","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/59be4066-7b6b-4296-aa3e-fdd01c2e1ff6"},{"id":"ef71230a-c6b7-4117-8367-36823ec29dab","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Staff Tech Lead Manager, Machine Learning, Simulator Evaluation ","slug":"staff-tech-lead-manager-machine-learning-simulator-evaluation-8931bbe0","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 About the Role \n Waymo’s simulator is one of the most complex virtual environments ever built, blending deterministic logic, physical dynamics, and state-of-the-art Generative AI to create a training ground for the Waymo Driver. Within this cutting-edge ecosystem, the Simulator Evaluation team faces the ultimate data challenge: How do you mathematically prove that a virtual world is \"real\"?\n While our team programmatically builds the metrics, pipelines, and ML systems that grade this hybrid environment, your challenge as a Staff Tech Lead Manager is to scale both this technology and the highly specialized team executing this vision. In this role, you will bridge technical vision and execution by translating cutting-edge generative AI advancements into production-ready evaluation tools used by engineering teams across Waymo to ensure the safety and performance of our autonomous fleet, while fostering an inclusive engineering culture of extreme technical rigor, rapid experimentation, and robust software quality.\n You will: \n \n Lead a top-tier applied ML team focused on building eval frameworks, infrastructure, and AI-powered tooling for World Model understanding and evaluation.\n Drive technical direction, and provide technical inputs and guidance to the team.\n Architect ML-driven metrics and evaluation frameworks that rigorously test World Model quality, automatically surfacing anomalies and edge cases across vast datasets.\n Chart the technical direction for World Model evaluation, working closely with Product and Program managers to translate modeling challenges into clear business objectives.\n Build AI-powered internal tools and products that streamline the model eval journey for users, transforming complex model analysis into intuitive, automated, fast-iteration workflows.\n Partner with cross-functional teams (e.g., Onboard, Research, and other Simulation teams) and senior technical leadership to deploy your team’s solutions into Waymo’s production-critical systems.\n \n You have: \n \n Degree in Computer Science, Robotics, Machine Learning, a related technical field, or equivalent practical experience\n 3+ years of hands-on technical leadership experience, directly managing and guiding high-performing engineering teams of 5-10 people\n 7+ years of experience building, deploying, and optimizing machine learning systems in production environments\n Strong software engineering proficiency in Python and/or C++\n Experience with ML frameworks like PyTorch, JAX, or Tensorflow, backed by a solid foundation in deep learning, transformers, and large-scale model deployment\n Proven ability to design robust evaluation frameworks for complex systems, combined with strong analytical skills and proficiency in large-scale data processing\n \n We Prefer: \n \n M.S. or PhD. in Computer Science, Robotics, Machine Learning, or a related quantitative field.\n A proven track record of training and/or evaluating large-scale generative models (e.g., reinforcement learning, diffusion, world models, 3D generative models, or video generation)\n Experience training and optimizing models on massive GPU/TPU clusters, and managing large-scale data processing/MLOps systems\n Experience building and deploying AI-powered products or internal developer tools that streamline or automate complex workflows\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 $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["mlops","robotics","reinforcement-learning","generative-ai","pytorch","tensorflow","autonomous-vehicles","deep-learning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8209790","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-17T18:34:35Z","expires_at":"2026-11-13T16:55:55.282713Z","created_at":"2026-10-14T15:20:04.74108Z","updated_at":"2026-10-14T16:55:55.286776Z","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/ef71230a-c6b7-4117-8367-36823ec29dab"},{"id":"81b7eb64-0dce-40b4-8980-aef38a717ee7","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Sr. Manager, Production, Air Maneuver Dominance","slug":"sr-manager-production-air-maneuver-dominance-7f9d68f3","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 JOB\n The Maneuver Dominance team at Anduril develops operationally relevant, multi-asset autonomy. We are focused on new air vehicle development programs, and making large groups of autonomous systems work effectively together.\n ABOUT THE JOB\n You will lead all production activity for an autonomous vehicle program within the Air Maneuver business line. You will build and lead the production organization from scratch, establishing manufacturing processes, quality systems, and the infrastructure needed to scale from prototype builds through full-rate production. Your spectrum of support will be diverse in nature and require you to leverage your technical expertise as well as leadership skills to set objectives, build cross-functional teams, and rapidly drive to completion. The ability to leverage your intuition and prior experience will be key in making sure the right design, analysis, and test steps are completed to ensure success. The ideal candidate will leverage their experience executing and successfully completing prior highly optimized multi-disciplinary projects.\n WHAT YOU'LL DO\n \n Own all production activity: manufacturing, quality, supply chain, and production support\n Build and lead the production organization, hiring across manufacturing engineering, quality, and operations\n Establish manufacturing processes and production infrastructure for complex electromechanical vehicles\n Drive the manufacturing development lifecycle: Concept, Prototype, LRIP, FRP\n Manage production budgets, schedules, and on-time delivery performance\n Own production readiness reviews and design handoff from engineering\n Coordinate supply chain including demand planning, procurement, and warehouse operations\n Implement and optimize production systems (ERP, MES, QMS)\n Drive continuous improvement using Lean, Six Sigma, or equivalent methodologies\n Ensure compliance with AS9100D and customer quality requirements\n Interface with engineering, program management, and customer organizations\n Travel up to 25% to manufacturing facilities and customer sites\n \n REQUIRED QUALIFICATIONS\n \n Bachelor's degree in Engineering, Manufacturing, Industrial Engineering, or equivalent\n 8+ years of experience in manufacturing or production for complex electromechanical systems\n Experience building and leading production teams and organizations\n Demonstrated experience scaling production from NPI through full-rate production\n Experience with production systems (ERP, MES, QMS)\n Ability to obtain and maintain a U.S. Secret security clearance\n \n PREFERRED QUALIFICATIONS\n \n Experience in maritime, aerospace, or defense manufacturing\n Working knowledge of AS9100D quality management systems\n Experience with Lean manufacturing and Six Sigma methodologies\n Familiarity with shipbuilding or large vehicle production\n Experience managing production budgets in the $10M+ range\n US Salary Range\n $166,000 — $220,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in m","salary_min":166000,"salary_max":220000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","cloud","payments","computer-vision"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5231782007?gh_jid=5231782007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-15T16:16:57Z","expires_at":"2026-11-13T16:57:16.632052Z","created_at":"2026-10-14T15:21:01.885426Z","updated_at":"2026-10-14T16:57:16.635114Z","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/81b7eb64-0dce-40b4-8980-aef38a717ee7"},{"id":"65abcedf-0783-4e19-9cf6-f8cb01fc1610","company_id":"63839083-85dd-4aa0-b128-254fc82866e5","title":"Software Engineer, Commercial Software","slug":"software-engineer-commercial-software-dd61b61a","description":"Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem.\n \nOn the Commercial Software team, we are building the platform that interfaces with the autonomous vehicle which enables customers and internal operations to manage fleet of trucks. We're a full stack web development team that works closely with our onboard team to integrate our platform and the vehicle, partners with the commercial team to build automated integrations with our customers' systems, and collaborate with design to create polished, seamless interfaces.\n \nYou will...\nBe part of a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale.\nBuild reliable and scalable tools and framework to support Autonomous Vehicle (AV) development.\nDevelop innovative solutions for challenging problems with scalable, production quality software.\nReceive hands-on work experience in identifying requirements, building and deploying software.\nWork closely and learn from the best developers in Autonomous Vehicles and Machine Learning.\nBuild a strong foundation of software development principles and patterns.\n \nQualifications:\nBachelor’s degree in Computer Science, Computer Engineering or related engineering disciplines.\n2+ years of industry experience developing production quality software.\nDemonstrated software engineering experience through internships, work experience, or coding competitions.\nProficient in reading and developing production quality software; experience with Go or Typescript.\nOpen-minded and collaborative team player with willingness to help others.\n \nBonus/ nice to have: \nExperience in one or more of the following areas: modern web technologies, distributed systems, data storage and processing, cloud infrastructures, test-driven and API-driven development methodologies, and system design/architecture. \nExperience in ML and self-driving.\nExperience working with robotics or machine learning research teams.\nExperience working in an Agile/Scrum environment.\n \nThe Canada yearly salary range for this role is: $149,000 - 220,000 CAD in addition to competitive perks \u0026 benefits. Waabi Canada Inc.s' yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all Canada locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.\n","salary_min":149000,"salary_max":220000,"location":"Toronto, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["distributed-systems","robotics","cloud","autonomous-vehicles"],"apply_url":"https://jobs.lever.co/waabi/6bcfed90-b577-4b09-a893-5c07186a1e0f/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-15T13:46:00.675Z","expires_at":"2026-11-13T16:56:19.911898Z","created_at":"2026-10-14T15:20:27.546684Z","updated_at":"2026-10-14T16:56:19.915153Z","company_name":"Waabi","company_slug":"waabi","company_logo_url":"https://www.google.com/s2/favicons?domain=waabi.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/65abcedf-0783-4e19-9cf6-f8cb01fc1610"}],"page":1,"per_page":20,"total":540,"total_is_exact":true,"total_pages":27}