[ engineering ]

Ml Infra Engineer, Data Systems

SeedBringing general-purpose AI into the physical worldPhysical intelligenceInvestment ThesisBetting on a ‘ChatGPT moment’ for robotics—led by Sergey Levine and Chelsea Finn, whose groundbreaking research now becomes reality.MilestoneLearn More →
Location
Not specified
Work mode
On-site
Type
full time
Listed
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[ About this role ]

ML Infra Engineer (Data Systems) at Physical Intelligence. This role involves building and operating data infrastructure for large-scale robot learning, focusing on data ingestion, processing, batch and streaming systems, storage, and lifecycle management. The engineer will optimize training-time performance and manage metadata for datasets and artifacts.

Skills and focus areas

  • distributed systems
  • storage systems
  • machine learning infrastructure
  • data ingestion
  • data processing
  • batch processing
  • streaming systems
  • object storage
  • metadata systems
  • data lifecycle management
  • performance optimization
  • data movement

Summary written by Ramai from the original posting. Full details and requirements are on SeedBringing general-purpose AI into the physical worldPhysical intelligenceInvestment ThesisBetting on a ‘ChatGPT moment’ for robotics—led by Sergey Levine and Chelsea Finn, whose groundbreaking research now becomes reality.MilestoneLearn More →’s careers page.

[ More at SeedBringing general-purpose AI into the physical worldPhysical intelligenceInvestment ThesisBetting on a ‘ChatGPT moment’ for robotics—led by Sergey Levine and Chelsea Finn, whose groundbreaking research now becomes reality.MilestoneLearn More → ]

See all 34 open roles at SeedBringing general-purpose AI into the physical worldPhysical intelligenceInvestment ThesisBetting on a ‘ChatGPT moment’ for robotics—led by Sergey Levine and Chelsea Finn, whose groundbreaking research now becomes reality.MilestoneLearn More → →

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