Senior Machine Learning Engineer, Discovery Recommendations

What Makes US Epic?

At the core of Epic's success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it's building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we're always innovating.

Being Epic means being a part of a team that continually strives to do right by our community and users. We're constantly innovating to raise the bar of engine and game development.

What We Do

Our Data & Analytics teams build powerful stories and visuals that inform the games we make, the technology we develop, and business decisions that drive Epic.

What You'll Do

• You will design, build, and optimize the recommendation systems that power Fortnite's Discover experience, serving personalized recommendations to one of the largest player bases in gaming across a massive catalog of creator-built experiences.
• You'll work across the full recommendation stack: candidate generation, content ranking, impression allocation, and real-time reranking.
• Unlike recommendation systems that operate over a stable catalog, you're working with a massive, rapidly changing content library where new experiences are published daily, quality signals are sparse, and the system's own outputs shape the data it learns from.

In this role, you will

• Design and implement retrieval, ranking, and reranking models for creator content using deep learning approaches (two-tower architectures, transformer-based sequence models, embedding-based retrieval) and build the user representation systems that power personalized discovery
• Build and optimize multi-stage candidate generation and impression allocation pipelines that balance relevance, diversity, and fair content exposure across a large and rapidly evolving catalog
• Design and run A/B experiments to validate model improvements, own evaluation frameworks that capture recommendation quality holistically, and drive the path from experiment to production deployment
• Collaborate with analytics and content quality teams on ranking signals including genre classification, creator credibility, and content quality metrics
• Own ML infrastructure decisions: choosing the right tradeoffs between batch, near-real-time, and streaming serving architectures

What we're looking for

• 5+ years of experience building production recommendation or ranking systems, ideally in a UGC, marketplace, or content discovery context
• Experience with deep learning for information retrieval and multi-stage recommendation pipelines (candidate generation, scoring, reranking)
• Demonstrated ability to design and analyze A/B experiments, with awareness of biases inherent to recommendation systems
• Strong Python engineering skills with experience in PyTorch and large-scale data processing frameworks (Spark preferred)
• Comfort working in a cloud-based ML environment
• Experience with explore/exploit strategies, content cold-start, or counterfactual evaluation methods applied to recommendation
• Experience with content understanding models (NLP, vision, or generative AI) used as ranking features
• Familiarity with creator economy dynamics and how recommendation design affects content quality and creator incentives
• Experience with our stack: PyTorch (TorchRec, Transformers), Ray, Databricks, AWS
• Passion for video games and/or experience with gaming analytics

Benefits

Epic Job + Epic Benefits = Epic Life:

• Our intent is to cover all things that are medically necessary and improve the quality of life.
• We pay 100% of the premiums for both you and your dependents.
• Our coverage includes Medical, Dental, a Vision HRA, Long Term Disability, Life Insurance & a 401k with competitive match.
• We also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents.

Throughout the year we celebrate our employees with events and company-wide paid breaks. We offer unlimited PTO and sick time and recognize individuals for 7 years of employment with a paid sabbatical.