{"id":185030,"url":"https://alion.io/job/physical-intelligence-ml-infra-engineer-modeling","title":"ML Infra Engineer, Modeling","company":{"id":48436,"name":"Physical Intelligence","domain":"pi.website","url":"https://alion.io/company/physicalintelligence","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":89,"open_postings":27,"ghost_share":0,"stale_share":0.444,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-10-17T05:46:00Z"}},"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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":165000,"max_usd":361000,"period":"year","method":"role_country_seniority_unknown","sample_n":4027},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"GCP","optional":false},{"name":"Google GKE","optional":false},{"name":"JAX","optional":false},{"name":"Kubernetes","optional":false},{"name":"PyTorch","optional":false},{"name":"SLURM","optional":false},{"name":"TPU","optional":false},{"name":"Multimodal AI","optional":true}],"status":"live","first_seen_at":"2026-09-01T01:09:51Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-17T05:43:55Z","board_verified":true,"closed_at":null,"days_open":46,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":46},"description":"Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\nIn this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments-and those experiments into production training runs.\nThis is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.\nThe Team\nThe ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.\nIn This Role You Will\nOwn training/inference infrastructure: Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.\n\nScale distributed training: Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.\n\nOptimize performance: Profile and improve memory usage, device utilization, throughput, and distributed synchronization.\n\nEnable rapid iteration: Build abstractions for launching, monitoring, debugging, and reproducing experiments.\n\nPartner with researchers: Translate research needs into infra capabilities and guide best practices for training at scale.\n\nContribute to core training code: Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.\n\nWhat We Hope You’ll Bring\nStrong software engineering fundamentals and experience building ML training infrastructure or internal platforms.\n\nHands-on large-scale training experience in JAX (preferred), PyTorch.\n\nFamiliarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.\n\nExperience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).\n\nAbility to debug and optimize performance bottlenecks across the training stack.\n\nStrong cross-functional communication and ownership mindset.\n\nBonus Points If You Have\nDeep ML systems background (e.g., training compilers, runtime optimization, custom kernels).\n\nExperience operating close to hardware (GPU/TPU performance tuning).\n\nBackground in robotics, multimodal models, or large-scale foundation models.\n\nExperience designing abstractions that balance researcher flexibility with system reliability.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.","description_format":"text","description_chars":3025,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotics AI","Foundation Models","AI Research Labs"],"lifecycle":[{"event":"open","at":"2026-09-01T13:56:25Z"}],"visa":[],"liveness":{"score":57,"band":"ok","label":"Likely open","p_open":1,"p_active":0.764,"p_room":0.75,"age_days":46,"expected_fill_days":55,"reasons":["conf:0","velocity","win:late"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/physical-intelligence-ml-infra-engineer-modeling","json_url":"https://alion.io/job/physical-intelligence-ml-infra-engineer-modeling.json","meta":{"generated_at":"2026-10-17T08:45:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":11720,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":48436},"rest":"https://alion.io/mcp/rest/get_company?id=48436"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fphysical-intelligence-ml-infra-engineer-modeling"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fphysical-intelligence-ml-infra-engineer-modeling"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fphysical-intelligence-ml-infra-engineer-modeling"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/physical-intelligence-ml-infra-engineer-modeling\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fphysical-intelligence-ml-infra-engineer-modeling"}]}