Senior Staff Machine Learning Platform Engineer

About Faire

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.

We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

Note: This role can also be performed remotely for candidates located in Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Utah, Virginia, Washington, or Wisconsin.

About this role

As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale. This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses.

What You Will Do

Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, governance

Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability

Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns

Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow

Optimize performance, reliability, and cost of the ML platform

Evaluate and integrate emerging Databricks features

Stay ahead of the curve by engaging with the latest developments in machine learning and AI

Serve as senior ML technical advisor to Faire’s data science and production engineering teams

Represent Faire at ML conferences and meetups

Mentor ML engineers and raise the overall bar for Machine Learning at Faire

What it takes

10-12 years of experience building and improving large-scale ML or data platforms.

A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field.

Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization

Proven ability to design systems that support multiple data science teams and production workloads

Strong background in distributed systems, ML infrastructure, and cloud architecture.

Demonstrated technical leadership across teams and orgs; ability to influence without authority