{"id":203870,"url":"https://alion.io/job/build-ai-lead-engineer-ml-data-infrastructure-systems","title":"Lead Engineer, ML Data Infrastructure & Systems","company":{"id":456056,"name":"Build AI","domain":"build.ai","url":"https://alion.io/company/build-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","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":{"min":220000,"max":350000,"currency":"USD","period":"year","gross":null,"usd_annual":350000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":true,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Linux","optional":false},{"name":"Python","optional":false},{"name":"AWS","optional":true},{"name":"Claude","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-08-30T03:09:32Z","employer_posted_date":"2026-08-30","last_verified_at":"2026-11-08T20:23:36Z","board_verified":true,"closed_at":null,"days_open":70,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":70},"description":"About Build AI\nBuild AI is the data hyperscaler for Physical AI. We're vertically integrated across hardware, manufacturing, logistics, collection, and model training to scale the physical labor dataset orders of magnitude faster than anyone in the world.\nJob Summary\nWe’re hiring a lead for the data platform: camera on a worker to training-ready datasets, and out to research customers. Collection is monocular 1920×1080p 30fps in the wild, targeting 100M hours. The roles we mean: Tesla Autopilot, Waymo, Cruise, Zoox, Nuro, Samsara, Verkada, Netflix encoding, YouTube ingest, Scale, Eventual/Daft. This is not a warehouse, analytics, or generic backend seat.\nKey Responsibilities\nOwn the data platform end-to-end: on-device capture, upload under flaky bandwidth, object storage, training-ready shards\n\nCompression, codecs, and storage-tier trade-offs so 1080p30 hours stay cheap enough to keep collecting\n\nUpload that survives bad networks: on-device buffering, batching, retries, a drop rate you can actually see\n\nObject storage and training-shard formats. The hard problem is petabyte-scale media, not a warehouse\n\nOwn dataset packaging, versioning, and delivery to external research customers\n\nWork with Shenzhen firmware so new devices speak one ingest contract, not a custom path per SKU\n\nMake health, cost, and drop rate obvious as we add sites and countries\n\nYou may be a good fit if you have (Must-have qualifications)\nYou have owned a production media or sensor data path at real scale: object storage at petabyte scale, video codecs and compression, upload under flaky bandwidth, or training-shard / dataset formats\n\nThat kind of data path: Tesla Autopilot, Waymo, Cruise, Zoox, Nuro, Samsara, Verkada, Netflix encoding, YouTube ingest, Scale, or Eventual/Daft. Demo-scale ETL is not this job\n\nStrong software engineering. Python and at least one systems language. Linux\n\nYou measure cost and throughput, not whether the demo uploaded\n\nYou want to scale in-the-wild physical-labor video, not run a generic data org\n\nStrong candidates may also have experience with (Nice-to-have qualifications)\nPose, multi-camera, or other large media besides video\n\nCloud (AWS or GCP), orchestration (Kubernetes, Airflow, Temporal), or IaC\n\nDataset management or annotation tooling\n\nYou have shipped dataset delivery to external research or training customers\n\nBenefits\nCompetitive pay\n\nMedical, dental, and vision packages with generous premium coverage\n\n$500 per month credit for waiving medical benefits\n\nHousing subsidy of $2k per month for those living within walking distance of the office\n\nRelocation support for those moving to San Francisco (Financial District) or Shenzhen (Nanshan)\n\nVarious wellness benefits covering fitness, mental health, and more\n\nDaily lunch and dinner in our office\n\nUnlimited compute budget subject to ROI justification\n\nUnlimited Codex and Claude credits\n\nTravel\n\nHow we're different\nBuild believes in the Bitter Lesson. By taking a general approach of learning from humans, our addressable market is all physical labor.\nWe are a fully in-person team in San Francisco (Financial District) and Shenzhen (Nanshan), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.\nBuild AI is an equal opportunity employer. We review every application. If you do not meet every bullet, still apply. 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