{"schemaVersion":"jobsearcher.job.v1","id":"ce90e8cec66bfd98d8a9f0ad","url":"https://jobsearcher.com/jobs/ce90e8cec66bfd98d8a9f0ad","canonicalUrl":"https://jobsearcher.com/jobs/ce90e8cec66bfd98d8a9f0ad","title":"Applied Scientist, Amazon Robotics, Compass Team","description":"Applied ScientistWe are seeking an Applied Scientist to join Compass. In this role, you will own the interface between contact-rich manipulation and the Compass safety software in unstructured environments. You will design learning-based and model-based approaches to contact-rich manipulation when the environment changes unexpectedly. You will collaborate with perception, planning, and controls teams to close the loop from object detection through grasp execution, and you will deploy your algorithms on physical hardware across multiple manipulator platforms. This is an opportunity to define how Amazon's robots safely interact with the physical world: picking, placing, and handling the enormous diversity of objects that flow through our network.Key job responsibilities:Develop and deploy manipulation algorithms for contact-rich tasks and placement across diverse object geometries and material propertiesDesign force-controlled manipulation strategies that operate safely within Amazon Compass safety constraintsBuild reactive manipulation policies that detect and recover from failures (slips, missed grasps, unexpected contacts) in real timeDevelop learning-based manipulation policies using RL, imitation learning, or hybrid approaches, and transfer them from simulation to physical hardwareDefine and maintain the interface contract between manipulation algorithms and the Compass safety layer, ensuring that grasp and motion plans respect safety bounds without unnecessary conservatismCollaborate with perception teams to leverage object pose estimation, tactile sensing, and contact detection for closed-loop manipulationDesign simulation environments and training curricula for manipulation policy learning, including realistic contact physics and object diversityEvaluate manipulation performance through systematic hardware experiments, measuring grasp success rates, cycle times, and safety complianceContribute to scientific publications and internal technical documentationParticipate in cross-team design reviews and contribute to the broader manipulation and safety architectureA day in the lifeAmazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: medical, dental, and vision coverage; maternity and parental leave options; paid time off; and a 401(k) plan.About the teamWork with the inventors of control barrier functions on a novel, universal approach to safe autonomy: one that scales across mobile robots, manipulators, mobile manipulators, and future robot platforms with dynamic stability. You'll push the boundary of safe performance by integrating safety with motion planning, RL, and foundation models, ensuring that safety is never a blocker to robot performance. Your work will underpin robots operating alongside people at Amazon's unprecedented scale.Basic qualifications:PhD, or Master's degree and 4+ years of CS, CE, ML or related field experienceExperience developing manipulation algorithms that have been tested on physical robot hardwareStrong understanding of contact mechanics, force control, and grasp planning fundamentalsProficiency in Python and C++ with experience in robotics software developmentExperience with at least one of: reinforcement learning for manipulation, imitation learning, or model-based grasp planningFamiliarity with physics simulators for contact-rich tasks (e.g., Isaac Gym/Sim, MuJoCo, Drake)Publication record at relevant venues (e.g., ICRA, IROS, RSS, CoRL, RA-L)Preferred qualifications:Experience in professional software developmentKnowledge of safety-critical control (control barrier functions, constrained optimization) as it applies to manipulationExperience with dexterous or multi-fingered manipulation and in-hand object reorientationExperience with sim-to-real transfer for contact-rich manipulation tasksExperience with compliant/impedance control and variable-stiffness actuationFamiliarity with foundation models or large-scale pre-training applied to manipulationExperience working with multiple manipulator platforms (industrial arms, collaborative robots, custom end-effectors)Exposure to functional safety concepts as they relate to human-robot interaction during manipulationStrong collaboration skills and experience working in cross-functional robotics teams","company":"Amazon Technologies","rawCompany":"amazon technologies","city":"Pasadena","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-07-08T00:41:28.027Z","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":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-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, Amazon Robotics, Compass Team","description":"Applied ScientistWe are seeking an Applied Scientist to join Compass. In this role, you will own the interface between contact-rich manipulation and the Compass safety software in unstructured environments. You will design learning-based and model-based approaches to contact-rich manipulation when the environment changes unexpectedly. You will collaborate with perception, planning, and controls teams to close the loop from object detection through grasp execution, and you will deploy your algorithms on physical hardware across multiple manipulator platforms. This is an opportunity to define how Amazon's robots safely interact with the physical world: picking, placing, and handling the enormous diversity of objects that flow through our network.Key job responsibilities:Develop and deploy manipulation algorithms for contact-rich tasks and placement across diverse object geometries and material propertiesDesign force-controlled manipulation strategies that operate safely within Amazon Compass safety constraintsBuild reactive manipulation policies that detect and recover from failures (slips, missed grasps, unexpected contacts) in real timeDevelop learning-based manipulation policies using RL, imitation learning, or hybrid approaches, and transfer them from simulation to physical hardwareDefine and maintain the interface contract between manipulation algorithms and the Compass safety layer, ensuring that grasp and motion plans respect safety bounds without unnecessary conservatismCollaborate with perception teams to leverage object pose estimation, tactile sensing, and contact detection for closed-loop manipulationDesign simulation environments and training curricula for manipulation policy learning, including realistic contact physics and object diversityEvaluate manipulation performance through systematic hardware experiments, measuring grasp success rates, cycle times, and safety complianceContribute to scientific publications and internal technical documentationParticipate in cross-team design reviews and contribute to the broader manipulation and safety architectureA day in the lifeAmazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: medical, dental, and vision coverage; maternity and parental leave options; paid time off; and a 401(k) plan.About the teamWork with the inventors of control barrier functions on a novel, universal approach to safe autonomy: one that scales across mobile robots, manipulators, mobile manipulators, and future robot platforms with dynamic stability. You'll push the boundary of safe performance by integrating safety with motion planning, RL, and foundation models, ensuring that safety is never a blocker to robot performance. Your work will underpin robots operating alongside people at Amazon's unprecedented scale.Basic qualifications:PhD, or Master's degree and 4+ years of CS, CE, ML or related field experienceExperience developing manipulation algorithms that have been tested on physical robot hardwareStrong understanding of contact mechanics, force control, and grasp planning fundamentalsProficiency in Python and C++ with experience in robotics software developmentExperience with at least one of: reinforcement learning for manipulation, imitation learning, or model-based grasp planningFamiliarity with physics simulators for contact-rich tasks (e.g., Isaac Gym/Sim, MuJoCo, Drake)Publication record at relevant venues (e.g., ICRA, IROS, RSS, CoRL, RA-L)Preferred qualifications:Experience in professional software developmentKnowledge of safety-critical control (control barrier functions, constrained optimization) as it applies to manipulationExperience with dexterous or multi-fingered manipulation and in-hand object reorientationExperience with sim-to-real transfer for contact-rich manipulation tasksExperience with compliant/impedance control and variable-stiffness actuationFamiliarity with foundation models or large-scale pre-training applied to manipulationExperience working with multiple manipulator platforms (industrial arms, collaborative robots, custom end-effectors)Exposure to functional safety concepts as they relate to human-robot interaction during manipulationStrong collaboration skills and experience working in cross-functional robotics teams","datePosted":"2026-07-08T00:41:28.027Z","dateModified":"2026-07-08T00:41:28.027Z","hiringOrganization":{"@type":"Organization","name":"Amazon Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Pasadena","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ce90e8cec66bfd98d8a9f0ad"},"url":"https://jobsearcher.com/jobs/ce90e8cec66bfd98d8a9f0ad"}}