Senior Staff Machine Learning Platform Engineer

Faire; San Francisco (CA); Hybrid; USD 295,000 - 405,500; Full time

Benefits offered by this job

Competitive pay

Equity

Comprehensive benefits

Job summary

Faire is seeking a Senior Staff Machine Learning Platform Engineer in San Francisco, CA. You will define the technical vision for our ML platform, set standards for architecture, and lead complex initiatives that enhance data science capabilities.

The ideal candidate will have over 10 years of experience in building ML platforms, a degree in Computer Science, and expertise in Databricks and cloud architectures. The role offers a hybrid work model and competitive compensation.

Qualifications

• 10-12 years of experience in large-scale ML or data platforms.
• Experience with Databricks lakehouse architecture, governance, and orchestration.
• Ability to design systems supporting multiple data science teams.

Responsibilities

• Define and drive architecture of the ML platform.
• Establish standards for code quality and MLOps.
• Mentor ML engineers to improve overall capabilities.

Skills

Machine Learning expertise

Cloud Architecture

Databricks lakehouse architecture

Distributed systems

Technical leadership

Education

Degree in Computer Science or related field

Tools

Python

SQL

AWS

Kubernetes

Job description

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

• 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.

Work Location and Schedule

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). 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.

Equal Employment Opportunity & Accessibility

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).