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Sr. Engineering Manager, MLOps

QuincePalo Alto, California, United StatesStorefront Engineering
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Salary
Not listed
Job type
Full-time
Posted
25 Mar 2026
Status
Open · checked 7d ago

About this role

The Senior Engineering Manager, MLOps position at Quince in Palo Alto, California, is a leadership role that directs machine learning infrastructure and guides a team of engineers to industrialize artificial intelligence at scale. This position is well-suited for a technical leader with a strong background in platform engineering who wants to shape the e-commerce technology stack.

Role Overview

Quince is seeking a Senior Engineering Manager, MLOps to architect and scale the production-grade infrastructure powering machine learning initiatives. This leader will own the end-to-end model lifecycle, transforming manual workflows into automated, self-service platforms for data scientists and AI researchers. Working in Palo Alto, California, the manager will balance high-performance training needs with cost governance, aligning technical roadmaps directly with e-commerce business outcomes like real-time personalization and inventory forecasting.

Key Responsibilities

Design and execute a long-term MLOps vision and strategy to transition ML workflows into a fully automated, self-service platform.
Build and maintain end-to-end infrastructure for model training, deployment, and serving to eliminate friction for researchers.
Partner with business leaders to align infrastructure investments with e-commerce drivers such as dynamic pricing and personalization.
Evaluate build versus buy decisions for cloud-native services and internal tools to optimize cost and flexibility.
Oversee the reliability, scalability, and performance of production machine learning services during high-traffic surges.
Direct the optimization of high-cost compute resources, including GPU clusters and cloud instances.
Recruit, mentor, and lead a high-performing team of machine learning infrastructure and DevOps engineers.
Drive the adoption of CI/CD standards for machine learning, Infrastructure as Code, and automated testing.
Serve as the primary cross-functional lead bridging the gap between AI research and engineering.
Establish key performance indicators for infrastructure velocity, deployment frequency, and cost per inference.

Requirements

Minimum of 10 years of professional industry experience, including 3 to 5 years in a leadership or management role focused on ML infrastructure, MLOps, or large-scale data platforms.
Proven track record of scaling MLOps platforms supporting data ingestion, distributed training, and real-time inference.
Deep technical expertise in cloud-native infrastructure, specifically AWS, and orchestration tools like Kubernetes, Docker, and Terraform or Pulumi.
Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Kubeflow, or SageMaker.
Expertise in building feature stores and high-throughput data pipelines using Spark, Flink, or Kafka.
Experience partnering with data science teams to translate research needs into scalable engineering solutions.
Strong understanding of CI/CD for machine learning, model versioning, and canary deployment strategies.
Demonstrated ability to manage GPU utilization and cloud spend in a hyper-growth environment.
Product-oriented mindset with strong communication and consensus-building skills.

Skills and Tools

PyTorch
TensorFlow
AWS
Kubernetes
Docker
Spark
LLM
MLOps
Kafka
Terraform

Salary and Benefits

The base pay range for this role is $270,000 to $300,000 USD, which may vary depending on experience level and location. Bonus and equity may also be provided for eligible roles.

About the Company

Quince operates a unique manufacturer-to-consumer model that eliminates traditional retail layers to offer high-quality essentials at lower prices. The company designs efficient operational processes and builds proprietary technology and analytics to scale rapidly across apparel, accessories, and home goods. Quince fosters a culture built for builders, encouraging team members to challenge conventional thinking and drive business impact regardless of their seniority.

How to Apply

Candidates should apply directly on the official Quince careers page.

Skills and tech stack

PyTorchTensorFlowAWSKubernetesDockerSparkLLMMLOpsKafkaTerraform

Questions candidates ask

What is the salary range for the Senior Engineering Manager, MLOps role?

The base salary range is $270,000 to $300,000 USD, with potential bonus and equity available for eligible roles.

Where is this job located?

This position is located in Palo Alto, California, United States.

What experience is required for this position?

Candidates must have 10+ years of industry experience, including at least 3 to 5 years in a leadership or management role focused on ML Infrastructure, MLOps, or large-scale Data Platform engineering.

What cloud platform and tools are primarily used?

The role utilizes AWS as the primary cloud-native infrastructure, alongside tools such as Kubernetes, Docker, Terraform, PyTorch, TensorFlow, Spark, and Kafka.

How should I apply for this job?

You should apply directly on the official Quince careers page.

Ready to apply?

The application is on the official Quince careers page.

Apply on company site