Senior Engineering Manager, Quince
MLOps
$270-300k
3+ days a week in office (Palo Alto, CA)
Affordable luxury fashion & home goods
Be an early applicant
Affordable luxury fashion & home goods
1001+ employees
Be an early applicant
$270-300k
3+ days a week in office (Palo Alto, CA)
1001+ employees
Company mission
To create products of equal or greater quality than the leading luxury brands at a much lower price.
Role
Who you are
- 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
- 10+ years of industry experience, with at least 3-5 years in a leadership or management role specifically focused on ML Infrastructure, MLOps, or large-scale Data Platform engineering
- Proven track record of building and scaling MLOps platforms that support the full model lifecycle—from data ingestion and distributed training to real-time inference and monitoring
- Deep technical expertise in cloud-native infrastructure (preferably AWS) and orchestration tools like Kubernetes (EKS), Docker, and Infrastructure as Code (Terraform/Pulumi)
- Hands-on experience with ML frameworks and tooling, such as PyTorch, TensorFlow, Kubeflow, or SageMaker, and a strong opinion on how to integrate them into a cohesive developer experience
- Expertise in building and managing Feature Stores and high-throughput data pipelines (using tools like Spark, Flink, or Kafka) to ensure data consistency across training and serving
- Experience partnering with AI Research and Data Science teams to understand their unique workflows and translate research needs into robust, scalable engineering solutions
- Strong understanding of CI/CD for ML, including automated testing for models, model versioning, and "blue-green" or "canary" deployment strategies
- Demonstrated ability to manage high-cost compute resources, with experience optimizing GPU utilization and cloud spend in a hyper-growth environment
- Excellence in operational leadership, with a history of driving service availability, performance, and stability through rigorous on-call rotations and root-cause analysis
- A product-oriented mindset, with the ability to treat infrastructure as a platform and prioritize the roadmap based on researcher velocity and business ROI
- Exceptional communication and influence skills, capable of navigating ambiguity and building consensus across engineering, product, and data science leadership
- Kindness and high standards: You move fast and push for excellence, but you do so as a supportive team player who fosters a culture of psychological safety and extreme candor
What the job involves
- We are seeking a Senior Engineering Manager, MLOps to join our growing team
- 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., SageMaker, 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 instances, balancing high-performance training needs with fiscal responsibility
- Recruit and Mentor Top Talent: Build and lead a high-performing team of ML Infra and DevOps engineers, providing technical coaching, career pathing, and performance management
- Establish MLOps Standards: Drive the adoption of best practices in CI/CD for ML, Infrastructure as Code (IaC), and automated testing to ensure a modular and maintainable system
- Bridge the Research-Engineering Gap: Act as the primary cross-functional lead, translating the complex needs of AI Researchers into actionable engineering requirements for the infrastructure team
- Define and Track Velocity Metrics: Establish KPIs for the infrastructure team, such as model deployment frequency, mean time to recovery (MTTR), and infrastructure cost per inference
- Champion Operational Excellence: Lead root-cause analyses (RCAs) for production failures and foster a culture of accountability where systemic fixes are prioritized over "quick patches."
- Stay Ahead of the AI Curve: Monitor emerging trends in LLM-ops, vector databases, and real-time feature engineering to ensure Quince’s infrastructure remains competitive and future-proof
Our take
Recently, there has been more widespread awareness of the alarming waste of resources and environmental impact caused by the fast fashion industry. Recognizing these concerns, Quince is looking to offer a more sustainable alternative to consumers.
Quince is a direct-to-consumer brand that offers high-quality products at lower prices by cutting out the middlemen. The company provides wardrobe staples and home goods, with an emphasis on minimalism, simplicity and timeless designs.
The company works directly with factories to produce inventory on a near-just-in-time basis. By eliminating unnecessary intermediaries, Quince can streamline the supply chain and reduce financial and environmental waste.
This approach allows Quince to ship goods directly to consumers' doorsteps, providing a more efficient and sustainable shopping experience. This has proven very popular, allowing the company to raise significant funding, reach a valuation of $4.5 billion and expand to Canada.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
58% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Mar 2026
$500m
SERIES E
Jul 2025
$200m
LATE VC
Total funding: $958m
Company HQ
SoMa, San Francisco, CA
Leadership
Sid Gupta
(CEO & Co-founder)Graduated from Stanford University with an MBA in Finance. Previously the Founder and CEO of Lolli and Pops as well as the Director of Strategy at TechTurn.
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job
View 19 more jobs at Quince