ML engineer - API Platform

Responsibilities

• Build Pi’s model API, including data ingestion, fine-tuning, evaluation, remote inference, partner-facing tools, and deployment integrations.
• Design reliable multi-tenant infrastructure that can scale to thousands of organizations and potentially millions of robots.
• Build and operate low-latency inference systems for models controlling robots in real-world environments.
• Develop product workflows from partner data upload and validation through processing, fine-tuning, and evaluation.
• Work with researchers to turn new model capabilities into stable APIs, tools, documentation, and abstractions.
• Write production code integrated with Pi’s infrastructure and define the developer platform for general-purpose robotics.

Requirements

• Strong software engineering fundamentals and experience building production systems.
• Deep backend and systems experience with APIs, services, databases, caching, distributed systems, and infrastructure.
• Experience building and scaling developer platforms, especially platforms for model fine-tuning, inference, or compute-intensive workloads.
• Understanding of reliability, latency, multi-tenancy, versioning, observability, and operational complexity at scale.
• Familiarity with deploying, serving, and debugging machine-learning models in production; ML research experience is not required.
• Strong Python skills and ability to work across infrastructure and product boundaries.
• Experience with low-latency or real-time systems, streaming, inference transport, WebSockets, QUIC, model serving, inference, fine-tuning, or developer-platform infrastructure is beneficial.
• Familiarity with Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, and TypeScript is beneficial.
• Experience with security, authentication, authorization, or multi-tenant infrastructure is beneficial.