{"id":717625,"url":"https://alion.io/job/fortyfive-software-engineer-simulation","title":"Software Engineer - Simulation","company":{"id":673507,"name":"FortyFive Labs","domain":"fortyfive.ai","url":"https://alion.io/company/fortyfive","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"D","score":40,"open_postings":13,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Backend","role_family":"Backend","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":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":130000,"max_usd":256000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1539},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Isaac Lab","optional":false},{"name":"MuJoCo","optional":false},{"name":"OpenAI","optional":false},{"name":"Physical AI","optional":false},{"name":"PyBullet","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Sim-to-Real","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Isaac Gym","optional":true},{"name":"Isaac Sim","optional":true}],"status":"live","first_seen_at":"2025-12-19T01:36:17Z","employer_posted_date":"2025-12-19","last_verified_at":"2026-10-27T21:52:35Z","board_verified":true,"closed_at":null,"days_open":312,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":312},"description":"Join Us in Building the Future of Physical AI\nWe build the simulation infrastructure for physical AI. We develop GenAI-powered tools that enable robotics teams to create unlimited, diverse training data and realistic evaluation environments. Our team spun out of MIT CSAIL, where we pioneered techniques that trained robots using only synthetic data. We're helping robotics companies transition to AI-native development workflows.\nWe're a lean team of researchers and engineers from DeepMind, OpenAI, FAIR, and top universities including MIT, Berkeley, Caltech, Harvard, and Yale. We've published best papers at top robotics conferences, won International Olympiad medals, and built core systems at leading AI labs. We believe in building complex systems that bring simplicity to our customers.\nGlobal Team: We operate across US and China time zones. We value people who communicate proactively, document thoroughly, and take ownership of smooth handoffs across teams.\nWhat to Expect\nWe're looking for a Simulation Engineer to build and scale our physics simulation infrastructure. You'll work on sim-to-real transfer, domain randomization, and creating training environments that enable robots to learn in simulation and perform in the real world.\nWhat You'll Do\nBuild and maintain simulation environments using MuJoCo, PyBullet, and Isaac Lab\n\nDevelop sim-to-real transfer pipelines and domain randomization systems\n\nCreate scalable infrastructure for parallel simulation execution\n\nDesign RL training environments with realistic physics and diverse scenarios\n\nCollaborate with ML researchers on environment design for policy learning\n\nWhat You'll Bring\n3-5 years of experience with physics simulation or robotics software\n\nProficiency with MuJoCo, PyBullet, Isaac Lab/Sim, or similar engines\n\nStrong Python skills; familiarity with C++ for performance-critical code\n\nExperience with reinforcement learning training pipelines\n\nUnderstanding of robot dynamics, kinematics, and control\n\nNice to Have\nExperience with sim-to-real transfer in deployed robotics systems\n\nBackground in domain randomization and synthetic data generation\n\nFamiliarity with GPU-accelerated simulation (Isaac Gym, Brax)\n\nPublications or projects in robot learning\n\nWe believe diverse teams build better products. 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