{"id":1931696,"url":"https://alion.io/job/humanoid-autonomy-engineer-vla-pre-training","title":"Autonomy Engineer - VLA Pre-training","company":{"id":35230,"name":"Humanoid","domain":"thehumanoid.ai","url":"https://alion.io/company/thehumanoid","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":12,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":56,"computed_at":"2026-10-12T06:55:09Z"}},"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 Diego, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":147000,"max_usd":279000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":414},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Edge AI","optional":false},{"name":"JAX","optional":false},{"name":"Post-training","optional":false},{"name":"Pre-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Vision-Language-Action","optional":false},{"name":"OpenVLA","optional":true}],"status":"live","first_seen_at":"2026-10-05T21:04:00Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-12T10:52:19Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND-01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.\nAbout the Role\nAs an Autonomy Engineer focused in VLA Pre-training, you will work on all aspects of training capable policies. You'll pre-train base models on a diverse, multi-embodiment corpus of trajectories, fine-tune policies to excel at specific tasks, shape data collection processes, and explore effective ways to generate and use synthetic data.\nThis is primarily a deep learning role, so we're looking for experience solving real-world problems with modern neural networks. Robotics experience isn't strictly required, but if you're coming from outside the field, be prepared to get up to speed on a new domain quickly.\nWhat You'll Do\nPost-train policies via behavior cloning and RL; own the full loop from data to deployment.\n\nPartner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage.\n\nWork closely with external partners to ensure steady supply of high-quality pretraining-scale data.\n\nRun pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes.\n\nBuild and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak-supervision labelling, curate balanced datasets, and auto-surface fresh failure cases into retraining.\n\nWork with MLOps & Data Platform teams to scale distributed training and optimize models for real-time edge inference.\n\nWhat We're Looking For\n3+ years building deep-learning systems (industry or research) with shipped models or published artifacts to show for it.\n\nDeep hands-on experience with at least one of: LLMs, VLMs, or image/video generative models - architecture, training, and inference.\n\nExperience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies.\n\nStrong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.\n\nFamiliarity with modern software engineering practices.\n\nYou document experiments clearly and communicate trade-offs crisply.\n\nNice to have\nRobotics or autonomous driving experience.\n\nExperience applying RL to LLMs or robotics.\n\nExperience with VLA (vision-language-action) models.\n\nProven productization of deep nets (latency/throughput constraints, telemetry, on-device optimization).\n\nPublications at top-tier deep learning conferences or equivalent open-source contributions.\n\nFamiliarity with OpenVLA, Physical Intelligence (π) models, or similar open source VLA frameworks.\n\nWhat We Offer\nComprehensive health coverage for US-based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.\n\nMeaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.\n\n401(k) retirement plan with employer match.\n\nEquity included-we believe builders should share in what they build.\n\nFree daily catered lunch, snacks, and drinks in-office.\n\nCollaboration with top-tier engineers, researchers, and product experts in AI and robotics.\n\nFreedom to influence the product and own key initiatives.\n\nFor this role in California, the expected base salary range is $180,000-$300,000 USD per year; 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