ML Engineer, Platform

Job description

Job 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.

Job requirements

• Experience building low-latency or real-time systems, including streaming, inference transport, WebSockets, QUIC, or similar technologies.
• Experience building model-serving, inference, fine-tuning, or developer-platform infrastructure.
• Experience at an early-stage infrastructure, AI, robotics, or autonomous systems company.
• Familiarity with our stack: Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, and TypeScript.
• Experience with security, authentication, authorization, or multi-tenant infrastructure.