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ML Engineer - API Platform

physicalintelligenceSan FranciscoSoftware Engineering
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Salary
Not listed
Job type
Full-time
Experience
Mid
Posted
5 Oct 2026
Status
Open · checked 7d ago

About this role

Based in San Francisco, this full-time role is for an API Product Engineer to build and scale model interfaces for physical intelligence applications. It suits software engineers with strong backend and systems backgrounds who want to develop developer platforms for general-purpose robotics.

Role Overview

Physical Intelligence is hiring an API Product Engineer in San Francisco to create the product surface that enables external developers and organizations to utilize foundational robotics models. The position involves designing the end-to-end platform for data ingestion, model fine-tuning, evaluation, and low-latency inference without requiring prior robotics experience.

Key Responsibilities

Build the complete model API covering data ingestion, fine-tuning, evaluation, low-latency remote inference, partner-facing tools, and deployment integrations.
Architect scalable multi-tenant infrastructure addressing rate limiting, isolation, backpressure, versioning, observability, and service level objectives.
Transform partner data pipelines into an intuitive product experience spanning upload, validation, processing, fine-tuning, and evaluation.
Develop and manage low-latency inference systems designed to control robots operating in real-world environments.
Collaborate directly with research teams to convert evolving model capabilities into stable product interfaces.
Address recurring user friction by improving APIs, tooling, documentation, and technical abstractions.
Write production-grade code that integrates with existing corporate infrastructure.

Requirements

Strong software engineering foundations with hands-on experience building production systems.
Deep backend and systems expertise covering APIs, services, databases, caching, distributed systems, and infrastructure.
Experience designing and scaling developer platforms, particularly for model fine-tuning, inference, or compute-intensive workloads.
Knowledge of large-scale system challenges such as reliability, latency, multi-tenancy, versioning, observability, and operational complexity.
Familiarity with machine learning systems to deploy, serve, and debug models in production environments.
Proficiency in Python to work across infrastructure and product boundaries.
High degree of ownership to independently solve ambiguous problems and build early-stage versions end-to-end.

Nice to Have

Experience creating low-latency or real-time systems using streaming, inference transport, WebSockets, or QUIC technologies.
Background in building model-serving, inference, fine-tuning, or developer platform infrastructure.
Previous tenure at an early-stage infrastructure, artificial intelligence, robotics, or autonomous systems organization.
Familiarity with the specific technology stack including Python, Postgres, ClickHouse, Google Cloud Platform, Kubernetes, Modal, React, and TypeScript.
Experience dealing with security, authentication, authorization, or multi-tenant infrastructure.

Skills and Tools

Python
Postgres
ClickHouse
GCP
Kubernetes
Modal
React
TypeScript
APIs and distributed systems

About the Company

Physical Intelligence develops foundation models and learning algorithms to power robots and physically-actuated devices. The software engineering group scales research breakthroughs into reliable physical products, bridging internal AI systems with external partners.

How to Apply

Candidates should apply directly on the official physicalintelligence careers page.

Skills and tech stack

PythonPostgresClickHouseGCPKubernetesModalReactTypeScriptWebSocketsQUICLLMMachine LearningFine-tuningDistributed Systems

Questions candidates ask

Is prior robotics experience required for this role?

No, robotics experience is not required. The company welcomes applicants who have built developer platforms, model APIs, or infrastructure products outside of robotics.

Where is the position located?

The role is located in San Francisco.

What programming languages and tools are associated with the tech stack?

The stack includes Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, and TypeScript.

Is this a customer success or partner support position?

No, this is not a customer success or partner support role, and it does not involve ongoing partner support or change management.

Do I need to be a machine learning researcher?

No, you do not need to be an ML researcher, though you should have enough familiarity with machine learning systems to deploy, serve, and debug models in production.

Ready to apply?

The application is on the official physicalintelligence careers page.

Apply on company site