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.

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

San Francisco: 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.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

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.

Why you’ll love working at Faire

Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.

Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.

Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.

Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.

Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.

Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog.

Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.

Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form)

Privacy

For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (https://www.faire.com/privacy)

Senior Staff Machine Learning Platform Engineer

Job Description

Skills & Requirements