Sr. Engineering Manager, MLOps

About Quince Founded in 2018, Quince is a direct‑to‑consumer tech company that disrupts retail with AI, analytics, and automation. 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 production‑grade Machine Learning infrastructure. 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. Responsibilities Define the MLOps Vision & Strategy. Own the "Paved Road" for Production. Drive Strategic Prioritization. Lead "Build vs. Buy" Evaluations. Guarantee System Scalability & Reliability. Manage Compute Governance & Costs. Recruit and Mentor Top Talent. Establish MLOps Standards. Bridge the Research‑Engineering Gap. Define and Track Velocity Metrics. Champion Operational Excellence. Stay Ahead of the AI Curve. Qualifications 10+ years of industry experience, with at least 3‑5 years in a leadership or management role 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. Deep technical expertise in cloud‑native infrastructure (preferably AWS) and orchestration tools such as Kubernetes, Docker, Terraform/Pulumi. Hands‑on experience with ML frameworks such as PyTorch, TensorFlow, Kubeflow, or SageMaker. Expertise in building and managing Feature Stores and high‑throughput data pipelines. Experience partnering with AI Research and Data Science teams. Strong understanding of CI/CD for ML, including automated testing, model versioning, "blue‑green" or "canary" deployment strategies. Demonstrated ability to manage high‑cost compute resources and optimize GPU utilization and cloud spend. Excellence in operational leadership with a history of driving service availability, performance, and stability. A product‑oriented mindset, treating infrastructure as a platform. Exceptional communication and influence skills, capable of navigating ambiguity and building consensus. Kindness and high standards, fostering a culture of psychological safety and extreme candor. Pay Range: $270,000 USD – $300,000 USD. Equal Opportunity & Hiring Integrity Quince provides equal employment opportunities to all employees and applies for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran or military status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Quince is committed to providing reasonable accommodations to qualified individuals with disabilities. Employment is contingent upon successful completion of a background check. Quince will conduct background checks in compliance with applicable federal, state, and local laws. #J-18808-Ljbffr Quince