Compensation Overview

Rec Room is the best place to build and play games together. Players can chat, hang out, play in millions of rooms, or build something new to share with the world! We have a vibrant commercial ecosystem within Rec Room, and our goal is to enable creators to be rewarded for their work. Come join us on the ground floor to help optimize the ecosystem for both players and the business.  

As the Lead Machine Learning Engineer focused on Personalization and Recommendations, you’ll be responsible for designing, developing, and implementing machine learning models to power our in-game store recommendations and serve users content that they’d find valuable. You’ll be supporting creators in making a living on the platform, as well as playing a critical role in the success of Rec Room as a business. 

WHAT YOU’LL DO:

• Design, develop and implement production-facing ML models to deliver valuable commerce content to our users.
• Collaborate closely with the ML Infra team to define a roadmap that powers real-time personalized ranking models.
• Design and run A/B tests, analyze model performance, and deep dive into the data to uncover opportunities for improvements.
• Build out pipelines in collaboration with our Analytics Engineering team to enable model building on top of sophisticated features.
• Set best practices, mentor, and provide guidance to the more junior Data Scientists.

WE ARE LOOKING FOR INDIVIDUALS WITH: 

• Master’s or Ph.D. degree in computer science, statistics, mathematics, or a related field
• 7+ years of ML experience in a production setting, with extensive experience working on ranking/recommendations
• Experience with recommendations, ranking, personalization, search, and/or content discovery
• Strong proficiency in Python and SQL
• Deep familiarity with ML infrastructure to collaborate with our infra team
• Extensive experience with experimentation.
• dbt knowledge is a plus
• Spark/Databricks knowledge is a plus