About Faire

Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. 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 that small businesses everywhere can compete with these big box and e-commerce giants.

By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. 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

Canada: the pay range for this role is $228,000 to $313,500 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

We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is taking part in the founding process.
We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.
We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.

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