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ML Engineer - API Platform

Physical Intelligence· Machine Learning
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San FranciscoFull-timePosted 2w ago

About the role

Physical Intelligence is building a platform to expose Pi’s models to external users via a developer-friendly API surface, enabling data ingestion, fine-tuning, evaluation, and low-latency inference at scale for robots and physically-actuated devices.

Responsibilities

  • Build Pi’s model API end to end, including data ingestion, fine-tuning, evaluation, low-latency remote inference, partner-facing tools, and deployment integrations.
  • Design systems that can scale from a small number of deeply integrated partners to thousands of organizations and potentially millions of robots.
  • Architect reliable, multi-tenant infrastructure around rate limiting, isolation, backpressure, versioning, observability, and SLOs.
  • Turn partner data into a first-class product experience, from initial upload through validation, processing, fine-tuning, and evaluation.
  • Build and operate low-latency inference systems that allow Pi models to control robots running in real-world environments.
  • Work closely with researchers to turn new model capabilities into stable, usable product surfaces.
  • Learn from how partners use the platform and turn recurring friction into better APIs, tooling, documentation, and abstractions.
  • Write high-quality production code that integrates deeply with Pi’s existing infrastructure.
  • Define what the developer platform for general-purpose robotics should look like.

Qualifications

  • Strong software engineering fundamentals and experience building production systems.
  • Deep backend and systems experience across APIs, services, databases, caching, distributed systems, and infrastructure.
  • Experience building and scaling developer platforms, especially for model fine-tuning, inference, or compute-intensive workloads.
  • Understanding of reliability, latency, multi-tenancy, versioning, observability, and operational complexity as systems scale.
  • Familiarity with deploying, serving, and debugging ML models in production (not required to be an ML researcher).
  • Strong Python skills and ability to work across infrastructure and product boundaries.
  • High degree of ownership and ability to turn ambiguous problems into end-to-end solutions.

Skills

Required:Software engineering fundamentalsBackend and distributed systemsDeveloper platform / model servingPython
Last updated Oct 7, 2026. Interested? Apply on the company site.
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About Physical Intelligence

Physical Intelligence (π)

Physical Intelligence is bringing general-purpose AI into the physical world.

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