ML Engineer, Platform

Job summary

Responsibilities

This is a software and systems role first. Robotics experience is not required, and we’re particularly excited about people who have built developer platforms, model APIs, or infrastructure products outside of robotics.

• 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.

What they're looking for

• 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. We’re especially interested in people who have shipped platforms for model fine-tuning, inference, or other compute-intensive…
• 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. You do not need to be an ML researcher.

Tech stack

• Python
• PostgreSQL
• GCP
• Kubernetes
• React
• TypeScript