Machine Learning Engineer (API Platform)
Confirmed on the employer's own hiring board on Oct 10, 2026. First seen by Alion on Oct 10, 2026. Π scores B on the Alion truth index.
Join Pi, a cutting-edge AI and robotics company, as a Machine Learning Engineer. In this role, you will work at the intersection of AI, infrastructure, and external partners. You will be responsible for building Pi's model API end to end, designing scalable systems, and turning partner data into a first-class product experience. You will also work closely with researchers to turn new model capabilities into stable, usable product surfaces. This is an exciting opportunity to shape the future of general-purpose robotics.
Missions
- 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.
- Architecturer une infrastructure multi-locataire fiable autour de la limitation de débit, de l'isolation, de la pression de retour, de la version, de l'observabilité.
- Travailler en étroite collaboration avec les chercheurs pour transformer les nouvelles capacités du modèle en surfaces de produit stables et utilisables.
Profil recherché
- Enough familiarity with machine learning systems to deploy, serve, and debug models in production. You do not need to be an ML researcher- An understanding of the problems that emerge as systems scale: reliability, latency, multi-tenancy, versioning, observability, and operational complexity
- Strong software engineering fundamentals and experience building production systems
- Strong Python skills and the ability to work comfortably across infrastructure and product boundaries
- 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
- Deep backend and systems experience across APIs, services, databases, caching, distributed systems, and infrastructure
- Experience with security, authentication, authorization, or multi-tenant infrastructure
- Familiarity with our stack: Python, Postgres, ClickHouse, GCP, Kubernetes, Modal, React, and TypeScript
- Experience building model-serving, inference, fine-tuning, or developer-platform infrastructure
- Experience at an early-stage infrastructure, AI, robotics, or autonomous systems company
- Experience building low-latency or real-time systems, including streaming, inference transport, WebSockets, QUIC, or similar technologies