ML Engineer - API Platform
Remote • San Francisco • FullTime
Posted 5h ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Product Engineer
About the job
Physical Intelligence is building foundation models and learning algorithms to power robots and physically-actuated devices. We are seeking an API Product Engineer to develop the product surface that enables external companies to utilize Pi's models, similar to how developers interact with LLM APIs today. This role involves owning the end-to-end experience of bringing models to life through a scalable platform, allowing partners to fine-tune models, evaluate them, and run low-latency inference within their own environments. You will transform capabilities that currently require close team collaboration into a platform designed to support a vast number of robots.
Responsibilities
- Build Pi's model API end-to-end, covering data ingestion, fine-tuning, evaluation, low-latency remote inference, partner tools, and deployment integrations.
- Design scalable systems to support thousands of organizations and potentially millions of robots.
- Architect reliable, multi-tenant infrastructure for rate limiting, isolation, backpressure, versioning, observability, and SLOs.
- Develop a first-class product experience for partner data, from upload through validation, processing, fine-tuning, and evaluation.
- Build and operate low-latency inference systems for Pi models to control real-world robots.
- Collaborate with researchers to translate new model capabilities into stable, usable product surfaces.
- Analyze partner platform usage to identify and address recurring friction points through improved APIs, tooling, documentation, and abstractions.
- Write high-quality production code that integrates deeply with Pi’s existing infrastructure.
- Define the future of developer platforms for general-purpose robotics.
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, particularly for model fine-tuning, inference, or compute-intensive workloads.
- Understanding of scaling challenges such as reliability, latency, multi-tenancy, versioning, observability, and operational complexity.
- Familiarity with machine learning systems for production deployment, serving, and debugging.
- Strong Python skills and ability to work across infrastructure and product boundaries.
- High degree of ownership and ability to take ambiguous problems from inception to a self-sustaining state.