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About the Role
As an API Product Engineer, you will 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.
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.
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.
- 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.
- 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.
Skills
- Python
- Backend development
- Systems engineering
- API development
- Distributed systems
- Infrastructure
- Developer platforms
- Model fine-tuning
- Model inference
- Low-latency systems
- Real-time systems
- Streaming
- WebSockets
- QUIC
- Model-serving infrastructure
- Security
- Authentication
- Authorization
- Multi-tenant infrastructure
Location
- Remote
Work Type
- Full-time
Experience Level
- Mid-level
- Senior
About the Company
- 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.
- 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.
Equal Opportunity
- Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.