Senior Staff Machine Learning Platform Engineer, Faire

$295-405.5k

+ Equity. Salary applicable to candidates based in CA

SQL

AWS

Docker

Kubernetes

Python

Kafka

Airflow

Kotlin

Terraform

MySQL

Spark

Unity

Snowflake

PyTorch

Sagemaker

Datadog

ChatGPT

Expert level

San Francisco Bay Area

Remote from US

More information about location

Online wholesale marketplace for retailers & brands

Open for applications

Online wholesale marketplace for retailers & brands

1001+ employees

RetailB2BMarketplaceSustainabilityConsumer GoodseCommerce

Open for applications

$295-405.5k

+ Equity. Salary applicable to candidates based in CA

SQL

AWS

Docker

Kubernetes

Python

Kafka

Airflow

Kotlin

Terraform

MySQL

Spark

Unity

Snowflake

PyTorch

Sagemaker

Datadog

ChatGPT

Expert level

San Francisco Bay Area

Remote from US

More information about location

1001+ employees

RetailB2BMarketplaceSustainabilityConsumer GoodseCommerce

Company mission

To empower brands and retailers to strengthen the unique character of local communities.

Job

Company

Role

Who you are

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
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
Claude Sonnet 4.5, ChatGPT 5.2

What the job involves

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
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

Our take

Faire is helping retailers find and buy wholesale merchandise for their stores, pairing independent brands with retailers. The company connects over 500,000 retailers globally to hundreds of thousands of brands across the globe.

In addition to a large catalog, the company attracts smaller retailers by offering net 60-day terms and free returns to boost confident buying at unpredictable times. Faire has seen impressive growth, reporting 300% year-on-year volume growth and a valuation of over $12.6B following its most recent tranche of funding from Shopify.

This investment is funding its continuing expansion into European and Australian markets, while accelerating product development, focusing on its OS for wholesale. It is also hiring talent globally as it takes aim at becoming a kind of Amazon for local and indie brands that want to sell globally.

Steph

Company Specialist at Welcome to the Jungle

Insights

Top investors

109% employee growth in 12 months

Glassdoor (3.8)

Trustpilot (4.6)

Company

Funding (last 2 of 11 rounds)

May 2022

$416m

SERIES G

Nov 2021

$400m

SERIES G

Total funding: $1.5bn

Company benefits

Comprehensive healthcare: Including Health, Dental, Vision and Disability for all our locations.
Time off: Paid time off, holidays and company-wide "Faire Fundays".
Parental leave: Generous parental and family leave, as well as fertility support benefits.
Productivity support: Monthly stipends to help cover work from home connectivity needs.
Annual learning grant: For personal and professional development, as well as unlimited access to training courses through LinkedIn Learning.
Thoughtfully designed spaces: All of our offices have been designed with local in mind – from our architects to our coffee blends.
Fitness and well-being benefits: Including monthly credit towards your wellness-related programmes.
Mental health benefits: Including free access to Modern Health therapists and resources.
Charitable matching: Faire will match up to £250 of your charity donations, every year.
Career planning: Whether you want to grow as a leader, hone your craft or explore a new discipline, our career framework allows space for you to explore.

Company HQ

Mission District, San Francisco, CA

Leadership

Max Rhodes

(Co-Founder & CEO)

Previously an Advisor at Blunt Umbrellas and a Director of Consumer Product at Square.

Marcelo Cortes

(Co-Founder & Chief Architect)

Previously a Senior Software Engineer at Google. Prior to that, they co-founded FreePoint Inc.

Jeff Kolovson

(Co-Founder & COO)

Previously an Operations Lead at Square. Prior to that, they were a Business Analyst for McKinsey and Co.

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