{"id":1452641,"url":"https://alion.io/job/fieldai-research-software-engineer-humanoid-whole-body-learning","title":"Research / Software Engineer - Humanoid Whole Body Learning","company":{"id":672883,"name":"FieldAI","domain":"fieldai.com","url":"https://alion.io/company/fieldai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":81,"open_postings":105,"ghost_share":0.229,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":61,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Boston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Imitation Learning","optional":false},{"name":"Isaac Lab","optional":false},{"name":"Isaac Sim","optional":false},{"name":"Machine Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Sim-to-Real","optional":false}],"status":"live","first_seen_at":"2026-09-29T03:41:03Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-21T10:10:47Z","board_verified":true,"closed_at":null,"days_open":22,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":22},"description":"FieldAI is seeking a Software/Research Engineer to help build the learning systems that power our next generation of humanoid robots. You'll work across whole-body loco-manipulation, reinforcement learning, motion retargeting, and real-world robot deployment, turning new research and technical developments into reliable capabilities on physical humanoids. This is a highly hands-on role for someone excited about closing the loop between research, simulation, and robots operating in the real world.\nWhat You Will Get To Do\nDevelop and train whole-body loco-manipulation policies for humanoid robots.\n\nDeploy trained policies to physical humanoids and integrate them into our production software stack.\n\nAdvance our motion retargeting pipeline, transforming human motion into physically plausible, robot-executable behaviors that interact with diverse environments and objects.\n\nReduce the sim-to-real gap by improving simulation fidelity and closing the real-to-sim loop, using real-world robot data to calibrate and refine our simulators.\n\nBuild automated evaluation and validation systems that make it faster and more reliable to move policies from simulation onto physical robots.\n\nImprove the performance and scalability of our robot-learning infrastructure, enabling faster experimentation and policy iteration.\n\nWork closely with researchers and engineers across perception, learning, simulation, and hardware to turn new ideas into deployed robot capabilities.\n\nWhat You Bring\nBS, MS, or PhD in Robotics, Computer Science, Machine Learning, Engineering, or a related field, or equivalent experience.\n\nExperience with reinforcement learning, imitation learning, generative models, or other learning-based approaches for robotics.\n\nStrong understanding of robotics fundamentals such as kinematics, dynamics, control, and physical interaction.\n\nExperience developing and evaluating robotic systems in simulation and/or on physical hardware.\n\nAbility to move comfortably between research experimentation and production-quality engineering.\n\nWhat Will Set You Apart\nHands-on experience with humanoid robots.\n\nExperience with whole-body loco-manipulation.\n\nExperience with GPU-accelerated simulation frameworks such as NVIDIA Isaac Sim, Isaac Lab, and/or Newton.\n\nExperience with motion retargeting.\n\nExperience taking learned robot behaviors from simulation to real hardware.\n\nExperience building scalable RL training, evaluation, and/or automated robot-testing infrastructure.","description_format":"text","description_chars":2482,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotics AI","Industrial AI"],"lifecycle":[{"event":"open","at":"2026-09-29T08:06:59Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 37","filings_12m":37,"filings_prev_12m":9,"green_card_filings_12m":0,"median_offered_wage_usd":162500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, 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