Staff Engineer, Machine Learning Infrastructure

quince · Palo Alto, California, United States · Palo Alto, California, United States

<div class="content-intro">ABOUT QUINCE Quince is a destination for builders, creators, innovators, and operators who want to come together and challenge the status quo. Our mission is simple: make really high quality essentials for really low prices, fairly and sustainably. We deliver on that mission through a unique manufacturer-to-consumer (M2C) model eliminating the layers of traditional retail that add cost and result in consumers paying more than they need to. We find, build relationships with, and work directly with the manufacturing partners behind some of the world’s finest products. From there, our teams design smart, efficient operational processes  and build and deploy proprietary technology, AI, and analytics to help us scale fast. What began with a small assortment of elevated basics has quickly grown into a cross-category brand spanning apparel, accessories, home goods, and more. Today, tens of millions of people across a growing number of countries come – and return – to Quince because they trust us to deliver. OUR CULTURE Quince is a culture built for builders by builders. Our way of working starts with a blank sheet of paper. We question conventional thinking, use technology and data to uncover new opportunities, and move quickly to turn ideas into reality. We aren’t interested in replicating how others do retail. We’re building a better way – at a speed and scale unlike anything that’s been done before. <ul> <li>We dream big and chase the hard problems others shy away from. Rejecting long-held assumptions is part of our company's DNA.  Where conventional wisdom says you have to choose – soft or durable, speed or rigor, quality or price – we ask why that trade-off has to exist in the first place.</li> <li>Our pace is fast and the bar is high because our customers expect a lot from us and we refuse to let them down. We believe the best results come from challenging ourselves, learning from one another, and building on each other's strengths. </li> <li>Here, responsibility is not determined by role, tenure, or seniority. Every team member - no matter their level - has the opportunity to drive our business and shape our trajectory. </li> </ul> If you’re someone who likes to imagine new possibilities and build better systems rather than plug-in to outdated ones, Quince is the place for you.</div>THE ROLE Staff Engineer, Machine Learning Infrastructure We are seeking a Staff Engineer, Machine Learning Infrastructure to join our growing team.  The ideal candidate is a deeply technical ML infrastructure engineer who combines hands-on mastery with system-level thinking. 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. Responsibilities <ul> <li>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.</li> <li>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.</li> <li>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 th

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