Principal Data Scientist - Foundational Models

Stitch Fix

About The Position

In this role, you will be building the next generation ML systems that transform the way people find what they love. As a Machine Learning Engineer, your focus will be on building, productionizing and scaling of machine learning models, and promoting engineering excellence. You will get the opportunity to work with data scientists, as well as lead work cross-functionally with Strategy, Product, Merchandising, Marketing, and Engineering partners to build and enhance those capabilities. You're excited about this opportunity because you will… Drive step-change improvements in machine learning models through novel research, large-scale experimentation, and production deployment. Bring your engineering excellence to improve how we serve real time recommendations in production at scale. Collaborate with data scientists on a variety of sophisticated machine learning algorithms Work closely with partners in ML Platform Eng, Engineering, Product and Merchandising teams Be empowered to take initiative and follow your innate curiosity

Requirements

You have 5+ years of experience developing or improving machine learning models and taking them from prototype to production.
You have 5+ years of advanced python development experience, including familiarity with data manipulation using spark and SQL.
You have a solid foundation in machine learning, plus a bonus of evaluating recommender systems.
You are familiar with modern ML frameworks (e.g. PyTorch, TensorFlow) and model deployment frameworks leveraging container orchestration.
You have hands-on experience with observability tools (e.g., Datadog, Prometheus) and a deep understanding of how to measure and optimize system latency.
You excel at translating complex technical concepts into clear, actionable insights for cross-functional partners, including Product, Design, and Engineering, to build consensus and drive projects forward.
You are driven by a deep curiosity to explore new technologies and take calculated risks, with a focus on identifying and implementing best practices that elevate the team's engineering standards.

Responsibilities

Drive step-change improvements in machine learning models through novel research, large-scale experimentation, and production deployment.
Bring your engineering excellence to improve how we serve real time recommendations in production at scale.
Collaborate with data scientists on a variety of sophisticated machine learning algorithms
Work closely with partners in ML Platform Eng, Engineering, Product and Merchandising teams
Be empowered to take initiative and follow your innate curiosity