About this role 

Faire is using machine learning to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced machine learning engineers and data scientists 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 technical lead of the Search & Recommendation team you’ll be responsible for developing systems that set the foundations required to enable real-time machine learning-powered search ranking models. You’ll determine answers to questions like, how can we scale our real-time pipeline to handle 3x the load? How fast we serve real-time embeddings of users' interests and use them to power rankings? How do these systems scale as we onboard more and more surfaces? What new techniques are emerging in the market that would empower our data scientists to do cutting-edge work? Our team already includes experienced Machine Learning Engineers and Data Scientists from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for MLE and data scientists, and you will help take us there! 

You’re excited about this role because… 

• You're passionate about building reliable, observable, maintainable and scalable systems 
• You’ll be able to work on cutting-edge systems that facilitate retrieval and ranking at scale such as Elasticsearch, Redis, and more! 
• You want to use machine learning to help local retailers and independent brands succeed 
• You want to be a critical Team Lead of a fast growing company 
• You like to solve challenging problems related to a two-sided marketplace 

Qualifications 

• 5+ years of industry experience in machine learning organizations building scalable machine learning model inference systems 
• Experience leading a team of machine learning engineers and managing project roadmapping with data, product, and other engineering teams 
• A history of mentoring other machine learning engineers, if not being a direct manager and scaling a team successfully 
• Strong communication skills and the ability to lead and work with others in a closely collaborative team environment 
• Strong fundamental programming skills such as Object oriented programming, systems design, functional programming 
• Experience with different types of data stores (relational databases, NoSQL databases, key-value stores)
• Strong machine learning background, experience in building and productionizing machine learning models 

Great to Haves: 

• Highly recommended: Master’s or PhD in Computer Science or Software Engineering or other related fields 
• Experience with numerous different backend and data tech stacks to understand the benefits and tradeoffs of various technologies