Sr. Engineering Manager, MLOps

About Quince

Founded in 2018, Quince was built to challenge the idea that nice things have to cost a lot. Our mission is simple: to make really high quality essentials for really low prices, produced fairly and sustainably. We believe everyone deserves exceptional craftsmanship and timeless design without the traditional markups. Quince is a direct‑to‑consumer (DTC) model that cuts out middlemen and leverages just‑in‑time manufacturing to minimize waste and maximize value.

Quince is a tech company disrupting the retail industry by putting AI, analytics and automation at the center of everything we do. Our unwavering commitment to excellence and company values guide our teams and actions:

• Customer First
  :
  We prioritize customer satisfaction in every decision.
• High Quality
  :
  True quality means premium materials and rigorous production standards you can feel good about.
• Essential Design
  :
  We focus on timeless, functional essentials instead of chasing trends.
• Always a Better Deal
  :
  Innovation and transparency ensure value for both customers and partners.
• Social & Environmental Responsibility
  :
  We commit to sustainable materials, ethical production, and fair wages.

At Quince, you will be part of a high‑performing team that is redefining what quality, value, and sustainability mean in modern retail. We are a destination for builders, innovators, and operators to come together and challenge the status quo. Our collective ambition is bold. We are creating an entirely new category and customer experience – one that democratizes luxury and provides high quality products at radically low prices.

That mission demands a world‑class team committed to excellence. If you are motivated by impact, growth, and purpose, you will find a strong sense of belonging at Quince.

Senior Engineering Manager, MLOps

We are seeking a Senior Engineering Manager, MLOps to join our growing team. The ideal candidate is a technical visionary with a proven track record of building and scaling the underlying infrastructure that powers production‑grade Machine Learning. You have a deep understanding of the ML lifecycle—from model development and distributed training to automated deployment and real‑time monitoring—and you are passionate about treating infrastructure as a product for your "customers":
Quince’s Data Scientists and AI Researchers. You are a self‑starter who excels at identifying architectural bottlenecks and transforming them into seamless, automated "paved roads" that increase team velocity without sacrificing stability. Thriving in an environment of rapid growth and ambiguity, you make high‑judgment decisions on "build vs. buy" and prioritize technical roadmaps that align directly with e‑commerce business outcomes. Above all, you are energized by a culture of distributed decision‑making and extreme candor, where you will lead a high‑performing team to set new standards for how AI is industrialized at scale to serve Quince customers.

• Define the MLOps Vision & Strategy:
  Architect a long‑term roadmap that transitions ML workflows from manual scripts to a fully automated, self‑service platform for all Quince Data Scientists and AI Researchers.
• Own the "Paved Road" for Production:
  Build and maintain the end‑to‑end infrastructure for model training, deployment, and serving, ensuring researchers can move from "idea to production" with zero friction.
• Drive Strategic Prioritization:
  Partner with business leaders to align infrastructure investments with core e‑commerce drivers like real‑time personalization, dynamic pricing, and inventory forecasting.
• Lead "Build vs. Buy" Evaluations:
  Make high‑judgment decisions on when to leverage cloud‑native services (e.g., Sage Maker, Vertex AI) versus building custom internal tools to optimize for cost, speed, and flexibility.
• Guarantee System Scalability & Reliability:
  Oversee the uptime and performance of production ML services, ensuring the stack can handle massive traffic surges and seasonal spikes without degradation.
• Manage Compute Governance & Costs:
  Direct the optimization of high‑cost computational resources, such as GPU clusters and cloud…