Machine Learning Engineer (API Platform)

Join Pi, a cutting-edge robotics company, as a Machine Learning Engineer (API Platform). In this role, you will build the product surface that allows other companies to use Pi's models, turning capabilities that require close collaboration with our team into a platform that can support thousands of robots. You will work closely with researchers and engineers to turn rapidly evolving model capabilities into APIs and tools that external users can build on. This is a software and systems role, and robotics experience is not required.

• Concevoir et construire l'API de modèle de Pi de bout en bout, y compris l'ingestion de données, le réglage fin, l'évaluation, l'inférence à faible latence, les outils orientés partenaires et les intégrations de déploiement.
• Architecturer une infrastructure fiable et multi-locataire autour de la limitation de débit, de l'isolation, de la pression de retour, de la version, de l'observabilité et des SLO.
• Travailler en étroite collaboration avec les chercheurs pour transformer les nouvelles capacités du modèle en surfaces de produit stables et utilisables.

• Deep backend and systems experience across APIs, services, databases, caching, distributed systems, and infrastructure
• Strong software engineering fundamentals and experience building production systems
• An understanding of the problems that emerge as systems scale: reliability, latency, multi-tenancy, versioning, observability, and operational complexity
• Strong Python skills and the ability to work comfortably across infrastructure and product boundaries
• Enough familiarity with machine learning systems to deploy, serve, and debug models in production. You do not need to be an ML researcher
• 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
• 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 workloads
• 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