Machine Learning Engineer III - FES

About Us

Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.

About The Team

We are the Fan Ecosystem Data team, responsible for enhancing decision-making and innovation across the entire Fanatics ecosystem through data and analytics. We build products that turn disparate data streams into real-time actionable insights, empowering teams to unlock greater value for our customers and stakeholders across every Fanatics surface.

We are seeking a Machine Learning Engineer III to own the infrastructure and systems that bring our data science models to life at scale. As our Data Scientists and Data Engineers build the models that understand and predict fan behavior, you build the platforms that serve those models in production.

Responsibilities

• Own the end-to-end ML infrastructure for recommendation, personalization, and LTV scoring systems, from feature engineering through model deployment and monitoring.
• Build and maintain real-time and batch feature pipelines that serve low-latency predictions across the FanApp recommendation experience and cross-vertical personalization use cases.
• Develop and scale model serving infrastructure that supports high-throughput, high-availability prediction across Fanatics' multi-product ecosystem.
• Partner directly with Data Scientists to productionize LTV, churn, propensity, and ranking models and bridge the gap between experimentation and reliable production systems.
• Build and maintain embedding pipelines that generate and refresh user and item representations powering personalization and affinity modeling at scale.