Machine Learning Engineer III

About the Company

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.

Responsibilities

• Own the end-to-end ML infrastructure for recommendation, personalization, and LTV scoring systems
• Build and maintain real-time and batch feature pipelines for low-latency predictions
• Develop and scale model serving infrastructure for high-throughput, high-availability prediction
• Partner with Data Scientists to productionize LTV, churn, propensity, and ranking models
• Build and maintain embedding pipelines for user and item representations
• Implement and maintain A/B testing and experimentation infrastructure
• Collaborate with Data Engineers and Product teams to ensure data quality and accurate signals
• Drive continuous improvement of model accuracy, latency, and throughput

Requirements

• 3–5+ years in machine learning engineering or data engineering
• Degree in a quantitative field (Computer Science, Mathematics, Statistics, Engineering)
• Strong Python proficiency and familiarity with production ML workflows
• Hands-on experience with ML platforms like Databricks or AWS SageMaker
• Experience building real-time feature pipelines and model serving systems at scale
• Experience scaling recommendation or ranking systems in production
• Solid understanding of distributed systems and large-scale data processing (Spark, Kafka)
• Strong SQL proficiency
• Practical understanding of linear algebra, probability, and optimization
• Familiarity with experimentation infrastructure and A/B testing frameworks

Preferred Qualifications

• Experience with feature stores (e.g., Feast, Tecton)
• Experience with ML observability tooling, including drift detection and prediction monitoring