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Physical Intelligence is building general-purpose AI for the physical world, developing foundation models and learning algorithms to power robots and physically-actuated devices. The company is now scaling its platform to make these models accessible to external users—developers, organizations, and hobbyists—similar to how LLM APIs work today.
In this role, you'll own the end-to-end API product experience that allows partners to bring their own data, fine-tune Pi's models, evaluate them, and run low-latency inference in their own environments. You'll transform capabilities that today require close collaboration with Pi's team into a self-service platform capable of supporting thousands and eventually millions of robots.
You'll work at the intersection of AI, infrastructure, and external partners, collaborating closely with researchers and engineers to turn rapidly evolving model capabilities into reliable, intuitive APIs and tools. The goal is to eliminate the significant hands-on work currently required to onboard new partners—making the process increasingly self-service and scalable.
Key responsibilities include:
- Building Pi's model API end to end: data ingestion, fine-tuning, evaluation, low-latency remote inference, partner-facing tools, and deployment integrations
- Designing systems that scale from a small number of deeply integrated partners to thousands of organizations
- Architecting reliable, multi-tenant infrastructure around rate limiting, isolation, backpressure, versioning, observability, and SLOs
- Turning partner data into a first-class product experience from upload through validation, processing, fine-tuning, and evaluation
- Building and operating low-latency inference systems for real-world robot control
- Working closely with researchers to stabilize and expose new model capabilities as product surfaces
- Learning from partner usage patterns and converting friction into better APIs, tooling, documentation, and abstractions
- Writing high-quality production code integrated with Pi's existing infrastructure
- Defining what the developer platform for general-purpose robotics should look like
This is a software and systems role first; robotics experience is not required. The company is particularly interested in people who have built developer platforms, model APIs, or infrastructure products outside robotics.
REQUIREMENTS:
- Strong software engineering fundamentals and production systems experience
- Deep backend and systems experience across APIs, services, databases, caching, distributed systems, and infrastructure
- Experience building and scaling developer platforms, especially for model fine-tuning, inference, or compute-intensive workloads
- Understanding of scaling challenges: reliability, latency, multi-tenancy, versioning, observability, and operational complexity
- Familiarity with machine learning systems to deploy, serve, and debug models in production (not required to be an ML researcher)
- Strong Python skills and ability to work across infrastructure and product boundaries
- High degree of ownership; comfortable taking ambiguous problems end to end and designing systems that don't depend on you
BONUS EXPERIENCE:
- Low-latency or real-time systems (streaming, inference transport, WebSockets, QUIC)
- Model-serving, inference, fine-tuning, or developer-platform infrastructure
- Early-stage infrastructure, AI, robotics, or autonomous systems companies
- Stack familiarity: Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, TypeScript
- Security, authentication, authorization, or multi-tenant infrastructure
