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Epic Games

Senior Machine Learning Engineer, Discovery Recommendations

Epic Games is hiring a Senior Machine Learning Engineer, Discovery Recommendations. Level rates it ; you can apply on Epic Games.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include PyTorch, Databricks and Python.
  • Level classifies it as a senior role.
  • Level lists 146 other open roles at Epic Games.
  • The role was posted in the last few days.

AI in this role

Design and optimize deep learning recommendation systems and ML infrastructure for Fortnite's Discover experience.

pytorchdatabrickspythontensorflowspark
nlpmachine-learningdeep-learningrecommendation-systemsa-b-testingmlops

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.

ANALYTICS

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

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.

ABOUT US

Epic Games​ ​is a leading interactive entertainment company. For over 30 years we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent.

Like what you hear? Come be a part of something Epic!

Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here.

Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will not pay any fees to any unauthorized third party. Further details on these matters can be found here.

How we rate this

Senior Machine Learning Engineer, Discovery Recommendations at Epic Games rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPMachine learningDeep learningRecommendation SystemsA B TestingMLOpsPyTorchDatabricks

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$195k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where deep learning was part of your work. What did you do?
  4. Tell me about a project where recommendation systems was part of your work. What did you do?
  5. Tell me about a project where a b testing was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: NLP, Machine learning, Deep learning, Recommendation Systems, and A B Testing. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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