ML Infra Engineer (Data Systems)

Physical Intelligence
San Francisco
Workplace: OnsiteFull timeFunction: Software EngineeringSkills: ["Ownership","Collaboration","Problem-solving","Communication","Attention to detail"]

Build and operate data infrastructure powering large-scale robot learning, bridging raw data sources to training and evaluation. You’ll design distributed data pipelines, storage layouts, and observability to ensure high performance, correctness, and reliability at scale, collaborating with researchers, engineers, and roboticists.

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FursaFursa
Physical Intelligence
Physical Intelligence
7 months ago

ML Infra Engineer (Data Systems)

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Source: Company careers pageValidated by: Fursa AI
Last checked: 18 hours agoStatus: Live

Job Summary

Build and operate data infrastructure powering large-scale robot learning, bridging raw data sources to training and evaluation. You’ll design distributed data pipelines, storage layouts, and observability to ensure high performance, correctness, and reliability at scale, collaborating with researchers, engineers, and roboticists.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering

Key Responsibilities

  • •Data Ingestion & Processing: Design and build high-throughput pipelines that validate, transform, and featurize raw multimodal data.
  • •Batch & Streaming Systems: Operate large-scale batch and streaming workflows over massive datasets.
  • •Storage Systems: Design object storage layouts, metadata systems, and efficient access patterns; choose file formats with performance and scalability in mind.
  • •Data Lifecycle Management: Build systems for backfills, dataset rebuilds, garbage collection, and large-scale transformations.
  • •Training-Time Performance: Optimize dataloaders, sharding, prefetching, caching, and throughput to reduce time from data arrival → model training.

Key Requirements

  • •Strong software engineering fundamentals.
  • •Experience building distributed systems or large-scale data pipelines.
  • •Comfort reasoning about performance, memory, I/O, and storage efficiency.
  • •Familiarity with batch and/or streaming processing systems.
  • •Experience with object storage systems and data format tradeoffs.
Experience:Data engineeringMachine learningDistributed systems
Skills:OwnershipCollaborationProblem-solvingCommunicationAttention to detail
Tech Stack:ClickHouseRayFlinkSparkObject storageDataloaderPetabyte-scale

Company Brief

Physical Intelligence
Develops large-scale AI models and learning algorithms to enable general-purpose intelligence for robots and physically-actuated devices, aiming to power a wide range of real-world robotic tasks and applications.
Industry: Robotics
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series B
Headquarters: San Francisco, United States
Founded: 2024
Glassdoor
Glassdoor: 4.1
WebsiteLinkedIn