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
• Experience integrating LLM workflows into enterprise platforms is a plus
• Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus

Tech Stack

Faire uses a modern cloud based tech stack. For this role, you'll want to be proficient with the following:

Category

Technologies

Languages

Python, SQL, Kotlin

ML Frameworks

PyTorch, PySpark, MLFlow

Big Data & Processing

Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL

Cloud & Infrastructure

AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform

Generative AI

Claude Sonnet 4.5, ChatGPT 5.2

Salary Range

California: the pay range for this role is $295,000 to $405,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.