ML engineer - API Platform

Physical Intelligence • San Francisco, CA

1d

About The Position

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.

Requirements

• 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. We’re especially interested in people who have shipped platforms for model fine-tuning, inference, or other compute-intensive workloads.
• An understanding of the problems that emerge as systems scale: reliability, latency, multi-tenancy, versioning, observability, and operational complexity.
• Enough familiarity with machine learning systems to deploy, serve, and debug models in production. You do not need to be an ML researcher.
• Strong Python skills and the ability to work comfortably across infrastructure and product boundaries.
• A high degree of ownership. You’re comfortable taking an ambiguous problem, building the first version end to end, and then designing the system so it no longer depends on you.

Nice To Haves

• 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.
• Experience at an early-stage infrastructure, AI, robotics, or autonomous systems company.
• Familiarity with our stack: Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, and TypeScript.
• Experience with security, authentication, authorization, or multi-tenant infrastructure.

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. There is no established playbook for this yet.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed