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Staff Engineer, Machine Learning Infrastructure

QuincePalo Alto, California, United StatesData Science
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Salary
$218K - $285K USD
Job type
Full-time
Posted
23 Jul 2026
Status
Open · checked 7d ago

About this role

The Staff Engineer, Machine Learning Infrastructure role at Quince is an on-site position based in Palo Alto, California, designed for experienced professionals who want to lead the creation of advanced ML platforms. This opportunity suits a technical expert with a passion for designing scalable, resilient, and high-performance machine learning systems within a fast-paced retail environment.

Role Overview

Quince is seeking a Staff Engineer, Machine Learning Infrastructure to join the Data Science team in Palo Alto, California. In this position, the professional will own the end-to-end technical design of the machine learning platform, encompassing training pipelines, serving infrastructure, feature pipelines, and monitoring systems. The ideal candidate combines hands-on mastery with system-level thinking to build production-grade ML systems at scale. By designing extensible and observable infrastructure, this engineer enables data scientists and AI researchers to move from ideas to production seamlessly.

Key Responsibilities

Architect the foundational machine learning infrastructure, ensuring modularity, scalability, and long-term extensibility for training, serving, feature pipelines, and monitoring.
Build the paved road for production by designing the core developer experience to help data scientists and AI researchers transition from idea to production with minimal friction.
Drive technical standards across the stack, implementing CI/CD for machine learning, Infrastructure as Code, model versioning, experiment tracking, and deployment strategies like blue-green and canary rollouts.
Evaluate and select core platform components, making build-versus-buy decisions for inference runtimes, feature stores, and orchestration frameworks.
Optimize compute performance and cloud costs by implementing GPU utilization strategies, model batching, and cost controls across workloads.
Ensure production scalability and reliability by architecting serving infrastructure that manages traffic surges, seasonal spikes, and model version transitions.
Provide technical mentorship to junior and mid-level engineers through design reviews, code reviews, and pairing sessions.
Lead root-cause analyses for production failures and champion operational excellence and rigorous on-call discipline.

Requirements

8+ years of total industry experience, including at least 4+ years of focused, hands-on work in machine learning infrastructure, MLOps, or large-scale data platform engineering.
Proven track record of designing and building MLOps platforms supporting the full model lifecycle from data ingestion to real-time inference and governance.
Deep expertise in cloud-native infrastructure, specifically AWS, Kubernetes, Docker, and Infrastructure as Code tools like Terraform or Pulumi.
Hands-on mastery of machine learning frameworks such as PyTorch, TensorFlow, Kubeflow, or SageMaker.
Expertise in building feature stores and high-throughput data pipelines using technologies like Spark, Flink, and Kafka.
Expert-level knowledge of CI/CD for machine learning, model versioning, experiment tracking, and deployment strategies.
Demonstrated ability to optimize GPU utilization, implement model batching, and reduce cloud infrastructure costs systematically.
Strong operational instincts with a history of improving reliability through proactive monitoring, on-call practices, and root-cause analysis.

Skills and Tools

PyTorch
TensorFlow
AWS
Kubernetes
Docker
Spark
MLOps
Kafka
Terraform

Salary and Benefits

Base salary pay range between $218,000 and $285,000 USD per year.
Bonus and equity may be provided for eligible roles.
Total compensation varies depending upon experience level and location.

About the Company

Quince is a destination for builders, creators, innovators, and operators challenging the conventional retail status quo. The company mission is to make high-quality essentials at low prices fairly and sustainably through a manufacturer-to-consumer model that eliminates traditional retail layers. Quince utilizes proprietary technology, AI, and analytics to scale fast across categories including apparel, accessories, and home goods. The company culture values building better systems, moving quickly, and rejecting long-held retail assumptions.

How to Apply

Interested candidates should visit the official Quince careers page to submit an application and review further details regarding the hiring process.

Skills and tech stack

PyTorchTensorFlowAWSKubernetesDockerSparkMLOpsKafkaTerraform

Questions candidates ask

What is the location of the Staff Engineer, Machine Learning Infrastructure role?

The position is located in Palo Alto, California, United States, and is an on-site role.

What is the salary range for this position?

The base salary range is $218,000 to $285,000 USD per year, with potential bonuses and equity available for eligible roles.

How many years of experience are required?

Candidates must have 8+ years of total industry experience, with at least 4+ years of focused, hands-on work in ML Infrastructure, MLOps, or large-scale data platform engineering.

What core technical skills are required?

Required skills include PyTorch, TensorFlow, AWS, Kubernetes, Docker, Spark, MLOps, Kafka, and Terraform.

How should I apply for this job?

You should apply directly on the official company careers page.

Ready to apply?

The application is on the official Quince careers page.

Apply on company site