ML engineer - API Platform

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ML engineer - API Platform in USA

Physical Intelligence
Full time
Email

USA
10/06/2026
Report

San Francisco, CA

Responsibilities

Build Pi’s model API, including data ingestion, fine-tuning, evaluation, remote inference, partner-facing tools, and deployment integrations.
Design reliable multi-tenant infrastructure that can scale to thousands of organizations and potentially millions of robots.
Build and operate low-latency inference systems for models controlling robots in real-world environments.
Develop product workflows from partner data upload and validation through processing, fine-tuning, and evaluation.
Work with researchers to turn new model capabilities into stable APIs, tools, documentation, and abstractions.
Write production code integrated with Pi’s infrastructure and define the developer platform for general-purpose robotics.

Requirements

Strong software engineering fundamentals and experience building production systems.
Deep backend and systems experience with APIs, services, databases, caching, distributed systems, and infrastructure.
Experience building and scaling developer platforms, especially platforms for model fine-tuning, inference, or compute-intensive workloads.
Understanding of reliability, latency, multi-tenancy, versioning, observability, and operational complexity at scale.
Familiarity with deploying, serving, and debugging machine-learning models in production; ML research experience is not required.
Strong Python skills and ability to work across infrastructure and product boundaries.
Experience with low-latency or real-time systems, streaming, inference transport, WebSockets, QUIC, model serving, inference, fine-tuning, or developer-platform infrastructure is beneficial.
Familiarity with Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, and TypeScript is beneficial.
Experience with security, authentication, authorization, or multi-tenant infrastructure is beneficial.

Physical Intelligence

Physical Intelligence builds general-purpose AI for the physical world, developing foundation models and full-stack robotic systems for robots and other actuated devices. The privately held company was founded in 2024 and focuses on taking designs from prototype to high-volume production, includi...

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