{"id":2968583,"url":"https://alion.io/job/roboforce-ai-resident","title":"AI Resident","company":{"id":686554,"name":"RoboForce","domain":"roboforce.ai","url":"https://alion.io/company/roboforce","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":82,"open_postings":14,"ghost_share":0.214,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":94,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Field & Service","role_family":"Field & Service","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Milpitas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":10000,"max":null,"currency":"USD","period":"month","gross":null,"usd_annual":120000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Embodied AI","optional":false},{"name":"Imitation Learning","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Physical AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Sim-to-Real","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vision-Language-Action","optional":false},{"name":"World Models","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Isaac Gym","optional":true},{"name":"Isaac Sim","optional":true},{"name":"MuJoCo","optional":true},{"name":"Post-training","optional":true}],"status":"live","first_seen_at":"2026-10-20T22:54:56Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-23T10:51:25Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":2},"description":"Why RoboForce\nRoboForce is an AI robotics company developing Physical AI-powered Robo-Labor for dull, dirty, and dangerous work. The company’s robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.\nThe AI Residency Program\nThe AI Residency Program is designed for exceptional early-career researchers and engineers who want to tackle some of the hardest problems in robotics and AI. Residents will work alongside a deeply technical team on core challenges in embodied physical intelligence, including Vision-Language-Action (VLA) models, World Models, World Action Models, and 3D foundation models, as well as the full stack of real-world learning-from efficient data collection systems and simulation to reinforcement learning and deployment on physical robots.\nThis is a hands-on residency for people who want to do ambitious work with real consequences: building learning systems that connect perception, reasoning, and action in service of capable, deployable robots. What makes this program different is the direct connection between research and real-world deployment. Residents work with actual RoboForce robots, iterate quickly between simulation and physical execution, and contribute to systems designed for real use.\nThe problems are hard, the standards are high, and the goal is to build systems that matter outside the lab.\nResearch Focus Areas\nAs an AI Resident, you may contribute across several core areas:\nVision-Language-Action (VLA) models for general-purpose robotic behavior\n\nWorld Models for predictive modeling, planning, and long-horizon decision-making\n\nWorld Action Models for jointly modeling action and environment dynamics\n\nSimulation and sim-to-real transfer for scalable training, evaluation, and data generation\n\nReinforcement learning, imitation learning, and policy optimization for embodied agents\n\nMultimodal learning across vision, language, proprioception, force, and action\n\nLearning systems for manipulation and real-world embodied interaction\n\nWhat You’ll Do\nConduct research and build systems for embodied physical intelligence\n\nDevelop and evaluate methods in VLA, World Models, World Action Models, simulation, and RL\n\nDesign and run experiments on robotics tasks involving perception, planning, control, and long-horizon behavior\n\nBuild training and evaluation pipelines for large-scale embodied learning systems\n\nWork closely with research and engineering teams to move ideas from prototype to real or simulated robot platforms\n\nExplore how multimodal foundation models can improve robot capability in real deployment settings\n\nContribute to technical reports, internal research discussions, and, where appropriate, publications\n\nBasic Qualifications\nPhD student, recent graduate, or early-career researcher/engineer in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field\n\nExperience with modern ML frameworks such as PyTorch, JAX, or TensorFlow\n\nExperience using AI-assisted coding tools and agentic development workflows to prototype, iterate, and build quickly\n\nAbility to implement, debug, and evaluate research ideas in a fast-moving environment\n\nStrong engineering judgment, including the ability to validate, refine, and productionize AI-assisted code\n\nPreferred Qualifications\nRich hands-on experience in robotic manipulation, mobile manipulation, or industrial robotics\n\nExperience training, fine-tuning, or evaluating multimodal or embodied models\n\nExperience with World Models, action-conditioned prediction, model-based learning, planning, or control\n\nStrong hands-on experience with simulation platforms such as Isaac Gym, Isaac Sim, MuJoCo, ManiSkill, Habitat, or similar systems\n\nExperience with reinforcement learning, imitation learning, or post-training for robotic policies\n\nExperience working with real robot hardware, data collection systems, evaluation workflows, or deployment pipelines\n\nDemonstrated technical initiative through research, open-source contributions, or high-impact engineering work\n\nCompensation and Resources\nDuration:\n3-6 months, full-time\nCompensation: \n$10,000 monthly salary\nBenefits:\nCompany-provided lunch and dinner, a fully stocked kitchen, and team events\n\nPremium fitness center membership covered by the company\n\nResources:\nAccess to large-scale GPU clusters and production-grade infrastructure, with dedicated support to enable fast, uninterrupted experimentation on ambitious robotics and AI workloads","description_format":"text","description_chars":4499,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotics AI","Industrial Robotics"],"lifecycle":[{"event":"open","at":"2026-10-21T01:13:10Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 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