Senior Machine Learning Engineer

Faire is using machine learning to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced data scientists and machine learning engineers are developing solutions related to discovery, ranking, search, recommendations, logistics, underwriting, and more - all with the goal of helping local retail thrive.

The Data team owns a wide variety of algorithms and models that power the marketplace. We care about building machine learning models that help our customers thrive.

As a Senior Machine Learning Engineer you’ll own develop and deploy machine learning models and help manage our machine learning platform that powers our systems. From the mobile checkout process, to personalized search ranking, to the intelligent underwriting engine that determines credit limits for retailers --- we are constantly iterating and innovating our product offering to create more value for the ecosystem

Our team already includes experienced Data Scientists and Machine Learning Engineers from Facebook, Uber, Airbnb, Square, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there!

What you will be doing:

• Leverage machine learning to optimize Faire’s two-sided marketplace dynamics
• Design, build and scale Real-Time and Batch processing pipelines to compute features, perform inference, and make decisions
• Improve Faire’s cutting-edge search & ranking problems combining a wide variety of data about our retailers, brands and products, or improve Faire's credit portfolio by evaluating creditworthiness of retailers on Faire’s platform; use predictive modeling to dynamically assign credit limits that minimize default risk and maximize growth 

Qualifications

• B.S., M.S., or PhD. in Computer Science or equivalent
• 3 years of industry experience on machine-learning teams
• Experience building and deploying various machine learning models
• Experience with modern back-end machine learning tech stacks
• Strong fundamental programming skills
  • Object-oriented design
  • Functional programming
  • Systems Design
• Solid understanding of engineering and infrastructure best practices, general software development principles with a machine learning software development life-cycle orientation
• An excitement and willingness to learn new tools and techniques
• Experience with relational databases and SQL
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves:

• Experience with DynamoDB, Redis, Elasticsearch, Kinesis Firehose, Redshift/Snowflake
• Experience with Java/Kotlin
• Experience working with complex systems at scale
  • Monitoring & Alerting
  • Performance analysis
  • Designing software for low latency and high through-put
• Experience training and launching machine-learning models