Physical Intelligence

Physical Intelligence

ML Engineer - API Platform

San Francisco

Sponsorship not specifiedDetected 11 days ago
PythonReactDistributed SystemsAlgorithmsPostgreSQLGCPKubernetesWebSocketsMachine LearningLLMsDesign SystemsCustomer SuccessRoboticsResearchCollaboration

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Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • IN THIS ROLE YOU WILL This is a software and systems role first.
  • There is no established playbook for this yet.
  • WHAT THIS ROLE IS NOT - This is not a Customer Success role.

Responsibilities

  • Design systems that can scale from a small number of deeply integrated partners to thousands of organizations and potentially millions of robots.
  • 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.
  • Learn from how partners use the platform and turn recurring friction into better APIs, tooling, documentation, and abstractions.
  • Strong software engineering fundamentals and experience building production systems.
  • Experience building and scaling developer platforms. We're especially interested in people who have shipped platforms for model fine-tuning, inference, or other compute-intensive workloads.
  • Experience building low-latency or real-time systems, including streaming, inference transport, WebSockets, QUIC, or similar technologies.
  • Experience building model-serving, inference, fine-tuning, or developer-platform infrastructure.
  • This is not a Customer Success role. You won't own ongoing partner support or change management inside customer organizations.
  • This is not a Partner Roboticist or Applied Research role. You won't be responsible for training policies for individual partners or debugging robots on site.

Requirements

  • Robotics experience is not required, and we're particularly excited about people who have built developer platforms, model APIs, or infrastructure products outside of robotics.
  • A high degree of ownership.
  • Experience with security, authentication, authorization, or multi-tenant infrastructure.

Benefits

  • Enough familiarity with machine learning systems to deploy, serve, and debug models in production.
  • 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.

Company info

  • 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.
  • We've made significant progress toward building models that can control many different robots across a wide range of tasks. Now, we're building the platform that will make those models accessible to the broader world.
  • As an API Product Engineer, you'll build the product surface that allows other companies to use Pi's models much like developers use an LLM API today: bring their own data, fine-tune models, evaluate them, and run low-latency inference in their own environments.
  • You'll own this experience end to end, turning capabilities that today require close collaboration with our team into a platform that can eventually support thousands-and ultimately millions-of robots.
  • Physical Intelligence is bringing general-purpose AI into the physical world.
  • Now, we're building the platform that will make those models accessible to the broader world.
  • Software Engineering at Pi builds the systems that scale research breakthroughs into reliable products in the physical world.
  • This role sits at the intersection of our AI, infrastructure, and external partners.
  • You'll work closely with researchers and engineers to turn rapidly evolving model capabilities into APIs and tools that external users, from hobbyists to large organizations, can actually build on.
  • Today, onboarding a new partner to Pi can involve significant hands-on work.
  • The goal is to make that increasingly unnecessary: partners should be able to bring us data, fine-tune a model, evaluate it, and run inference through a product that is intuitive, reliable, and built to scale.
  • The goal is to make that increasingly unnecessary:
  • partners should be able to bring us data, fine-tune a model, evaluate it, and run inference through a product that is intuitive, reliable, and built to scale.
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