{"id":679252,"url":"https://alion.io/job/mindrobotics-research-engineer","title":"Research Engineer","company":{"id":678470,"name":"Mind Robotics","domain":"mindrobotics.com","url":"https://alion.io/company/mindrobotics","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":79,"open_postings":28,"ghost_share":0.357,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":48,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":163000,"max_usd":363000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"VLM","optional":false},{"name":"Embodied AI","optional":true}],"status":"live","first_seen_at":"2026-01-26T17:50:44Z","employer_posted_date":"2026-01-26","last_verified_at":"2026-11-03T12:17:31Z","board_verified":true,"closed_at":null,"days_open":280,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":280},"description":"About Mind:\nMind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.\nAbout the team and the role:\nAt Mind Robotics, we’re building generalized physical AI -robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. Our ability to iterate quickly on large-scale models depends on world-class ML infrastructure.\nWe’re looking for a Research Engineer to build the core systems that enable fast, reliable, and scalable model training-powering everything from experimentation to production deployment.\nResponsibilities:\nDesign and implement scalable systems for training large ML models.\n\nEnable efficient workflows for data ingestion, training, and iteration.\n\nDevelop and optimize distributed training systems across hundreds of GPUs.\n\nImplement strategies for parallelization, sharding, and efficient compute utilization.\n\nImprove training efficiency through techniques such as attention optimizations, kernel fusion, and memory management.\n\nPartner closely with modeling teams to accelerate iteration speed and reduce training costs.\n\nBuild internal tools for experiment tracking, monitoring, and debugging.\n\nImplement systems for tracking training performance, failures, and resource utilization.\n\nDebug and resolve bottlenecks across the training stack.\n\nProvide lightweight infrastructure support for deploying and running models in production environments.\n\nOptimize inference performance and reliability where needed.\n\nSupport core cloud infrastructure needs for training workloads (without heavy DevOps overhead).\n\nManage compute resources efficiently across training jobs.\n\nRequirements:\nStrong experience building infrastructure for large-scale ML training.\n\nDeep understanding of how modern LLM/VLM systems are trained and scaled.\n\nProven experience setting up and scaling distributed training across hundreds of GPUs.\n\nStrong understanding of parallelization strategies (data, model, pipeline parallelism).\n\nStrong proficiency in Python programming.\n\nExpert-level proficiency in PyTorch and/or JAX.\n\nStrong understanding of techniques like attention optimization, kernel fusion, and efficient memory usage.\n\nNice to Have:\nExperience supporting 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