{"id":429064,"url":"https://alion.io/job/relari-research-engineer-human-biomechanics","title":"Research Engineer, Human Biomechanics","company":{"id":183616,"name":"Relari","domain":"relari.ai","url":"https://alion.io/company/relari","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Work at a Startup","truth_index":{"grade":"A","score":100,"open_postings":3,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-01T06:10:25Z"}},"role":"AI/ML","role_family":"AI/ML","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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":125000,"max":175000,"currency":"USD","period":"year","gross":null,"usd_annual":175000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-09-06T05:34:57Z","employer_posted_date":"2026-10-31","last_verified_at":"2026-11-02T01:55:55Z","board_verified":true,"closed_at":null,"days_open":56,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":56},"description":"About the role\nYou will bring a deep understanding of human movement and physical interaction into the same research loop as our robot-learning engineers. You will design experiments and computational representations spanning muscle activity, force, pressure, tactile contact, motion, and touch feedback. The goal is to determine which structure can be measured reliably and transferred across people, tasks, sensors, and robot embodiments. This is an engineering role: ideas should become code, datasets, models, and robot experiments.\nWhat you’ll do\nDevelop signal-processing and learning methods for synchronized EMG, force, tactile, pressure, motion, and visual data.\nDesign experiments and sensor configurations that capture how humans regulate contact, stability, coordination, and effort during manipulation.\nBuild multimodal representations that connect neuromuscular activity with external forces and touch feedback.\nDevelop calibration and domain-adaptation methods that remain reliable across people, sessions, tasks, and sensor configurations.\nCreate data-collection protocols grounded in biomechanics and downstream robot-learning needs.\nWork with robot-learning researchers to test whether physical-interaction representations improve policy behavior and cross-embodiment transfer.\nInfluence wearable sensing, force and tactile hardware, validation procedures, and future measurement systems.\nWhat we’re looking for\nResearch or engineering depth in biomechanics, neuroengineering, biomedical engineering, motor control, computational neuroscience, haptics, kinesiology, or a related field.\nHands-on experience collecting and analyzing one or more forms of biomechanical or physiological data, such as EMG, force, pressure, tactile sensing, motion capture, or wearable-sensor data.\nStrong quantitative skills in signal processing, statistics, time-series modeling, sensor fusion, or machine learning.\nFluency in Python and the ability to build reliable modeling pipelines around imperfect, synchronized sensor data.\nInterest in connecting human physical interaction with learned robot behavior; a PhD is welcome but not required when equivalent depth is demonstrated through other work.\nWorking at Relari\nRelari is a small research and engineering startup developing new ways for robots to learn dexterous skills from human biomechanics. Our founders have AI research roots at MIT and NVIDIA, along with autonomous-vehicle and robotics deployment experience at Pony AI and Dexterity. We are backed by top investors including Y Combinator, General Catalyst, and Soma Capital. You will work directly with the founders, own problems end to end, and test your ideas on real robotic systems. 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