{"id":3574600,"url":"https://alion.io/job/tutor-intelligence-robotics-research-scientist-san-francisco-ca","title":"Research Scientist, Robotics","company":{"id":5788,"name":"Tutor Intelligence","domain":"tutorintelligence.com","url":"https://alion.io/company/tutorintelligence","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":89,"open_postings":35,"ghost_share":0,"stale_share":0.229,"repost_share":0,"time_to_fill_p50_days":135,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Robotics","role_family":"Robotics","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":420000,"currency":"USD","period":"year","gross":null,"usd_annual":420000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Imitation Learning","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SFT","optional":false},{"name":"Vision-Language-Action","optional":false},{"name":"Reward Modeling","optional":true}],"status":"live","first_seen_at":"2026-10-31T17:41:42Z","employer_posted_date":"2026-10-31","last_verified_at":"2026-11-05T21:12:10Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About Tutor\nWe believe robots are the biggest lever we have to making the physical world a better, more affordable place. But robots are a rounding error in our society: nearly nine out of ten American factories and warehouses don’t even have a single robot, and robots have yet to make their way into our homes or places of business.\nTutor Intelligence is changing that.\nTutor is a robotics research and deployment company, building generally capable robot hardware and artificial intelligence to enable robots to go where no robots have gone before. Sonny is a semi-humanoid robot with frontier dexterity approaching the human form. Cassie does back-breaking work, moving boxes, pallets, and bulk goods for businesses from family-owned manufacturers to some of the largest brands in the world. Tutor robots are manufactured at scale and operate as a network, combining the whole fleet’s learned experience to train ever more capable robot artificial intelligence.\nFounded at MIT and headquartered in Watertown, MA, our team is full stack: we design and manufacture robot hardware, train our own models, work directly with the smallest and largest end-customers, and maintain our fleet across the United States. We’re a team of researchers, engineers, technicians, operators, and sellers who love building things and solving hard problems.\nOur mission is grand: robots everywhere, for the common good, raising the standard of living across North America, and then the world.\nThe Role\nTutor's research team pushes the frontier of robot capability across the full stack. Researchers have access to 100+ robots for data collection and evaluation, a massive network of teleoperators, scaled hardware and manufacturing infrastructure, and the ability to collect real world data at enormous scale. Our work covers the complete lifecycle of real-world data generation and model training from initial behavior cloning to post-training with supervised fine-tuning and reinforcement learning. And researchers and research engineers work closely with applied engineers to develop novel techniques into robot products that can be deployed at scale.\nAs a research scientist, you'll set the direction for how our robots learn.\nWhat you'll work on\nSet research directions in robot learning for dexterous manipulation, from framing the problem to results that hold up on robots.\nDevelop methods that learn from large-scale human supervision: teleoperated demonstrations, interventions and corrections, and human feedback used as reward.\nDesign experiments across the DF1 fleet, and build the evaluations that separate a real improvement from noise.\nTrain and post-train vision-language-action models with behavior cloning, supervised fine-tuning, and reinforcement learning.\nWork with research and applied engineers to turn new techniques into models that run on deployed Cassie and Sonny robots.\nShare results through internal write-ups and technical reports.\nRequirements\n5+ years of research experience in robot learning, machine learning, or a related field, through a PhD or equivalent industry experience.\nA track record of original work in robot learning, imitation learning, reinforcement learning, or large-model training, shown through publications, open-source work, or shipped systems.\nStrong Python and hands-on experience with PyTorch or JAX.\nExperience running experiments on physical robots, not only in simulation.\nClear communication of results, including the negative ones.\nNice to haves\nVision-language-action models, or diffusion and flow-matching policies.\nLearning from human feedback, interventions, or reward modeling.\nBimanual or dexterous manipulation.\nLarge-scale distributed training.\nNot afraid to step foot in a factory or a 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