Sr. Engineering Manager, MLOps

Quince
Palo Alto
Workplace: OnsiteFull timeUSD 270,000 - 300,000 annuallyFunction: Software EngineeringSkills: ["Communication","Leadership","Influence","Mentoring"]

Senior Engineering Manager leading ML Operations and infrastructure for production-ready ML systems in a fast-growing retail/tech environment. You’ll define a vision for MLOps, own end-to-end production pipelines, drive strategic prioritization aligned with e-commerce goals, evaluate build-vs-buy decisions, and ensure scalable, reliable ML infrastructure powering researchers and customers at scale.

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Quince
Quince
4 months ago

Sr. Engineering Manager, MLOps

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Job Summary

Senior Engineering Manager leading ML Operations and infrastructure for production-ready ML systems in a fast-growing retail/tech environment. You’ll define a vision for MLOps, own end-to-end production pipelines, drive strategic prioritization aligned with e-commerce goals, evaluate build-vs-buy decisions, and ensure scalable, reliable ML infrastructure powering researchers and customers at scale.
Location: Palo Alto
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Sr. Manager level

Key Responsibilities

  • •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.

Pay and Benefits

Salary: USD 270,000 - 300,000 annually

Key Requirements

  • •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:AI/MLE-commerceRetail
Skills:CommunicationLeadershipInfluenceMentoring
Languages:English
Tech Stack:AWSKubernetesEKSDockerTerraformPulumiPyTorchTensorFlowKubeflowSageMakerSparkFlinkKafka

Company Brief

Quince
Quince is a direct-to-consumer brand offering affordable, high-quality apparel, home goods, and essentials—such as cashmere, basics, and home textiles—focused on transparent sourcing and value pricing for customers.
Industry: Direct to Consumer Brands
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Headquarters: San Francisco, United States
Founded: 2015
WebsiteLinkedIn