{"id":121267,"url":"https://alion.io/job/dexmate-robot-learning-engineer-2","title":"Robot Learning Engineer","company":{"id":6958,"name":"Dexmate","domain":"dexmate.com","url":"https://alion.io/company/dexmate","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":90,"open_postings":33,"ghost_share":0.091,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":169,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Robotics","role_family":"Robotics","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Fremont, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":100000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Drake","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Isaac Gym","optional":false},{"name":"Isaac Sim","optional":false},{"name":"JAX","optional":false},{"name":"MuJoCo","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"TensorFlow","optional":false},{"name":"Sim-to-Real","optional":true}],"status":"live","first_seen_at":"2025-12-15T12:42:28Z","employer_posted_date":"2025-12-15","last_verified_at":"2026-10-16T23:45:00Z","board_verified":true,"closed_at":null,"days_open":305,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":304},"description":"About Dexmate\nDexmate is building the foundation for physical AI - combining a new generation of robots with a universal Physical AI OS, making robots as easy to build and deploy as software. Today, robotics is fragmented, slow, and closed: most builders are forced to reinvent the same stack again and again, and most ideas never make it past the prototype stage. We exist to change that. Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI.\nIf you want to help shape the next layer of human capability - and believe the future of robotics should be built together, not in isolation - we'd love to build it with you.\nThe Role\nWe are looking for Robot Learning Engineers to build the learning systems that give our robots new skills. You will design and deploy reinforcement learning, imitation learning, and foundation-model approaches for manipulation, navigation, and control - from simulation through deployment on physical robots.\nResponsibilities\nDesign and implement state-of-the-art learning algorithms for robot manipulation, navigation, and control-from simulation to deployment on physical systems\n\nDevelop novel approaches to enhance robot dexterity and mobility using reinforcement learning, imitation learning, and foundation models, etc.\n\nScale ML systems for large-scale model training and fine-tuning.\n\nBuild diverse, robust manipulation skills that push the boundaries of what robots can do\n\nCollaborate closely with hardware, controls, and systems engineers to create integrated solutions\n\nMinimum Qualifications\nPhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or related field; OR Master's degree with 1+ years industry experience; OR Bachelor's degree with 3+ years industry experience\n\n2+ years of hands-on experience developing AI systems for robotics applications\n\nDeep expertise in modern robot learning techniques (reinforcement learning, imitation learning, behavior cloning, etc.)\n\nStrong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX)\n\nProven experience conducting real robot experiments and debugging complex robotic systems\n\nExperience with robot simulators (Isaac Gym, Isaac Sim, MuJoCo, SAPIEN, Drake, or similar)\n\nExcellent problem-solving abilities and strong communication skills\n\nGenuine passion for robotics and building products that work in the real world\n\nPreferred Qualifications\nPublications at top robotics/ML conferences (RSS, CoRL, ICRA, IROS, NeurIPS, ICLR, etc.)\n\nExperience with vision-language models or foundation models for robotics\n\nFamiliarity with sim-to-real transfer techniques and domain randomization\n\nExperience with distributed training and MLOps 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