{"schemaVersion":"jobsearcher.job.v1","id":"e69f9ca1b9c63b5b6786b3f8","url":"https://jobsearcher.com/jobs/e69f9ca1b9c63b5b6786b3f8","canonicalUrl":"https://jobsearcher.com/jobs/e69f9ca1b9c63b5b6786b3f8","title":"Applied Scientist, Navigation","description":"Job ID: 10451675 | Amazon.com Services LLC\n\nAmazon is on a mission to redefine the future of automation. We are building the next generation of advanced robotic systems that seamlessly blend AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real‑world environments.\n\nAs a Scientist in Robot Navigation, you will architect and deliver navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning‑based planning and control, foundation models, and control‑theoretic approaches such as model predictive control (MPC). Your work will blend data‑driven intelligence with principled control‑theoretic guarantees.\n\nKey Responsibilities\n\nDesign, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding.\n\nLead research initiatives in computer vision, sensor fusion, and 3D perception.\n\nCollaborate with cross‑functional teams (robotics engineers, software engineers, product managers) to define and deliver perception capabilities.\n\nDrive end‑to‑end ownership of ML models—from data collection and labeling strategy to training, evaluation, and deployment.\n\nMentor junior scientists and engineers; contribute to a culture of technical excellence.\n\nDefine and track key metrics to measure perception system performance in real‑world environments.\n\nPublish research findings in top‑tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents.\n\nA Day in the Life\n\nTrain ML models for deployment in simulation and on real‑world robots, and identify & document post‑deployment limitations.\n\nDrive technical discussions within your team and with stakeholders to develop innovative solutions to identified limitations.\n\nActively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed.\n\nMentor team members while maintaining significant hands‑on contribution to technical solutions.\n\nTeam Overview\nOur team is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action, learning from failure and iterating quickly toward solutions that matter.\n\nBasic Qualifications\n\nExperience programming in Java, C++, Python, or related language.\n\nPhD in Robotics, Computer Science, Electrical Engineering, Controls, or related field.\n\n2+ years of experience in robot navigation, motion planning, or autonomous systems.\n\nDeep expertise in learning‑based approaches to navigation (e.g., imitation learning, reinforcement learning, neural motion planning, diffusion‑based policies).\n\nStrong experience with Model Predictive Control (MPC) and optimization‑based planning (PyTorch, JAX, or equivalent).\n\nProven track record of translating research into deployed systems.\n\nPreferred Qualifications\n\nExperience applying foundation models or large pre‑trained models to robotics tasks (navigation, manipulation, or embodied AI).\n\nFamiliarity with world models, visual navigation, or vision‑language action models.\n\nExperience with sim‑to‑real transfer and high‑fidelity simulation environments (Isaac Sim, MuJoCo, Gazebo).\n\nKnowledge of SLAM, localization, and mapping systems.\n\nExperience with ROS/ROS2 and real‑time robotics middleware.\n\nHands‑on experience deploying navigation systems on physical robots in dynamic, real‑world environments.\n\nExperience with safety‑critical systems and formal verification of learned controllers.\n\nFamiliarity with multi‑agent coordination and fleet‑level navigation.\n\nBenefits and Compensation\nLocation: San Francisco, CA – $171,600.00 – $222,200.00 USD annually; Reading, MA – $142,800.00 – $193,200.00 USD annually.\n\nThe base salary range is listed below. Your package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance, dental, vision, prescription coverage, Basic Life & AD&D insurance, supplemental life plans, EAP, mental health support, Medical Advice Line, Flexible Spending Accounts, adoption and surrogacy reimbursement coverage, 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.\n\nEqual Opportunity Employer\nAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Pursuant to the Los Angeles County Fair Chance Ordinance and the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.\n\n#J-18808-Ljbffr","company":"Amazon","rawCompany":"amazon","city":"Reading","state":"MA","isRemote":false,"isActive":false,"createdAt":"2026-06-24T03:15:35.535Z","occupations":[{"code":"17-2199.08","title":"Robotics Engineers","slug":"robotics-engineers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"17-3024.01","title":"Robotics Technicians","slug":"robotics-technicians"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"333248","title":"All Other Industrial Machinery Manufacturing","slug":"all-other-industrial-machinery-manufacturing"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Applied Scientist, Navigation","description":"Job ID: 10451675 | Amazon.com Services LLC\n\nAmazon is on a mission to redefine the future of automation. We are building the next generation of advanced robotic systems that seamlessly blend AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real‑world environments.\n\nAs a Scientist in Robot Navigation, you will architect and deliver navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning‑based planning and control, foundation models, and control‑theoretic approaches such as model predictive control (MPC). Your work will blend data‑driven intelligence with principled control‑theoretic guarantees.\n\nKey Responsibilities\n\nDesign, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding.\n\nLead research initiatives in computer vision, sensor fusion, and 3D perception.\n\nCollaborate with cross‑functional teams (robotics engineers, software engineers, product managers) to define and deliver perception capabilities.\n\nDrive end‑to‑end ownership of ML models—from data collection and labeling strategy to training, evaluation, and deployment.\n\nMentor junior scientists and engineers; contribute to a culture of technical excellence.\n\nDefine and track key metrics to measure perception system performance in real‑world environments.\n\nPublish research findings in top‑tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents.\n\nA Day in the Life\n\nTrain ML models for deployment in simulation and on real‑world robots, and identify & document post‑deployment limitations.\n\nDrive technical discussions within your team and with stakeholders to develop innovative solutions to identified limitations.\n\nActively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed.\n\nMentor team members while maintaining significant hands‑on contribution to technical solutions.\n\nTeam Overview\nOur team is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action, learning from failure and iterating quickly toward solutions that matter.\n\nBasic Qualifications\n\nExperience programming in Java, C++, Python, or related language.\n\nPhD in Robotics, Computer Science, Electrical Engineering, Controls, or related field.\n\n2+ years of experience in robot navigation, motion planning, or autonomous systems.\n\nDeep expertise in learning‑based approaches to navigation (e.g., imitation learning, reinforcement learning, neural motion planning, diffusion‑based policies).\n\nStrong experience with Model Predictive Control (MPC) and optimization‑based planning (PyTorch, JAX, or equivalent).\n\nProven track record of translating research into deployed systems.\n\nPreferred Qualifications\n\nExperience applying foundation models or large pre‑trained models to robotics tasks (navigation, manipulation, or embodied AI).\n\nFamiliarity with world models, visual navigation, or vision‑language action models.\n\nExperience with sim‑to‑real transfer and high‑fidelity simulation environments (Isaac Sim, MuJoCo, Gazebo).\n\nKnowledge of SLAM, localization, and mapping systems.\n\nExperience with ROS/ROS2 and real‑time robotics middleware.\n\nHands‑on experience deploying navigation systems on physical robots in dynamic, real‑world environments.\n\nExperience with safety‑critical systems and formal verification of learned controllers.\n\nFamiliarity with multi‑agent coordination and fleet‑level navigation.\n\nBenefits and Compensation\nLocation: San Francisco, CA – $171,600.00 – $222,200.00 USD annually; Reading, MA – $142,800.00 – $193,200.00 USD annually.\n\nThe base salary range is listed below. Your package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance, dental, vision, prescription coverage, Basic Life & AD&D insurance, supplemental life plans, EAP, mental health support, Medical Advice Line, Flexible Spending Accounts, adoption and surrogacy reimbursement coverage, 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.\n\nEqual Opportunity Employer\nAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Pursuant to the Los Angeles County Fair Chance Ordinance and the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.\n\n#J-18808-Ljbffr","datePosted":"2026-06-24T03:15:35.535Z","dateModified":"2026-06-24T03:15:35.535Z","hiringOrganization":{"@type":"Organization","name":"Amazon","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Reading","addressRegion":"MA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e69f9ca1b9c63b5b6786b3f8"},"url":"https://jobsearcher.com/jobs/e69f9ca1b9c63b5b6786b3f8"}}