Machine Learning Engineer, Memory

Epic Games, Inc.

City Of London

On-site

GBP 90,000 - 150,000

Full time

14 days+

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Benefits offered by this job

Pension
Private medical insurance
Health care cash plan
Dental insurance
Disability insurance
Life insurance
Critical illness
Cycle to work
Flu shots
Health checks
Meals

Job summary

Epic Games is seeking a Machine Learning Engineer focused on memory to advance memory-driven models across our Unreal Engine and platform ecosystem. You will collaborate with researchers to define general memory solutions, decide what to retain or discard, and build robust, scalable systems that store, retrieve and exploit experience effectively.

Ideal candidates have a PhD or 3+ years in industry with ML work on memory, context, or long-horizon methods, plus strong Python and ML tooling skills

Qualifications

  • PhD in Computer Science, Mathematics or related field or 3+ years of relevant industry experience.
  • Experience creating machine learning algorithms for vision and/or language problems and deploying them as production-level systems.
  • Expert, hands-on knowledge of foundational models and vision and/or language, incl. local deployment and model post-training of open weights models.
  • Memory, state, or long-horizon behaviour in foundation models: from language agents to long-context methods and sequence modelling.
  • Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch).
  • Experience collaborating with other developers in a flexible, agile environment.

Responsibilities

  • Design memory architectures that work across problems, modalities and products.
  • Define new metrics to measure memory performance.
  • Deliver production-ready, scalable learning models and guiding algorithms.
  • Assess effectiveness and provide recommendations for the product roadmap.

Skills

ML algorithms (vision/lang)
Python & ML tools
Memory/long-horizon models
Agile & collaboration

Education

PhD in Computer Science, Mathematics or related field

Tools

PyTorch
NumPy
SciPy
Scikit-learn

Job description

Machine Learning Engineer, Memory

2026-10-14T00:00:00

London

Greater London

GB

EC2V 8

Any

Epic Games

2026-11-17T10:00:35.34

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 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.

ENGINEERING - GAMES
What We Do

Unreal projects have been leading the pack of real-time entertainment with our constantly growing team of engineering experts. We're always improving on the tools and technology that empower content developers worldwide.

What You'll Do

As foundation models move from answering questions to acting over long horizons, memory becomes a central requirement. Systems must decide what is worth keeping and improve from experience. Large context windows and retrieval systems are not enough. You will work with researchers on projects across the company that require memory in different modalities to define general solutions that enable models to represent experience, decide what they keep and what they discard, and to efficiently store, retrieve and exploit memory.

In this role, you will:

  • Design new memory architectures that work across problems, modalities and products
  • Define new ways to measure and evaluate memory performance
  • Help create and deliver production-ready, scalable and high-quality learning models and associated algorithms
  • Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap
What we’re looking for
  • PhD in Computer Science, Mathematics or related field, or 3+ years of relevant industry experience
  • Experience creating machine learning algorithms for vision and/or language problems and deploying them as production-level systems
  • Expert, hands‑on knowledge of: Foundational models and vision and/or language, incl. local deployment and model post‑training of open weights models
  • Memory, state, or long‑horizon behaviour in foundation models: your experience may come from language agents and long‑context methods, reinforcement learning under partial observability, world models, or sequence modelling
  • Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)
  • Experience with working collaboratively with other developers, following a flexible and agile approach
EPIC JOB + EPIC BENEFITS = EPIC LIFE

We pay 100% for benefits except for PMI (for dependents). Our current benefits package includes pension, private medical insurance, health care cash plan, dental insurance, disability and life insurance, critical illness, cycle to work scheme, flu shots, health checks, and meals. We also offer a robust mental well‑being program through Modern Health, which provides free therapy and coaching for employees & dependents.

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, but it is also a tool being embraced by content creators across 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 assemble 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.

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