Staff Engineer (Machine Learning Infrastructure)

Description du poste

We are seeking a Staff Engineer, Machine Learning Infrastructure to join our growing team You have built and operated production-grade ML systems at scale — from distributed training pipelines and feature stores to high-throughput inference serving — and you take pride in engineering platforms that other engineers love to use You don’t just build for today’s requirements; you design for extensibility, observability, and resilience You are the kind of engineer who gravitates toward the hardest problems — whether that’s optimizing GPU utilization at the tail of the cost curve, designing a zero-downtime model deployment system, or defining the architectural patterns that will define how Quince industrializes AI at scale You operate with high autonomy, hold yourself to exceptional standards, and elevate the engineers around you through code reviews, technical mentorship, and by setting a bar for what great looks like Architect the ML Infrastructure Foundation: Own the end-to-end technical design of Quince’s ML platform — including model training, serving, feature pipelines, and monitoring — ensuring it is modular, scalable, and built for long-term extensibility Build the “Paved Road” for Production: Design and implement the core developer experience for Quince’s Data Scientists and AI Researchers, enabling them to move from “idea to production” with minimal friction and maximum reliability Drive Technical Excellence Across the Stack: Set and uphold engineering standards in CI/CD for ML, Infrastructure as Code (IaC), model versioning, experiment tracking, and deployment strategies (blue-green, canary) — and build the tooling that makes those standards the path of least resistance Own High-Impact System Design Decisions: Lead the technical evaluation and selection of core platform components — from inference runtimes and feature stores to orchestration frameworks — with a clear-eyed view of build vs. buy tradeoffs Optimize Compute Performance & Cost: Design and i

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