Machine Learning Ops Engineer

Epic Games
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist, Machine Learning Engineer, Data Analyst, Data Engineer, AI Engineer, Business Intelligence Analyst, Data Architect, Analytics Engineer, Research Data Scientist, Statistician, Quantitative Analyst, ML Ops Engineer, Applied Scientist, Insigh

Machine Learning Engineer

Senior Machine Learning Engineer (MLOps)

Senior Machine Learning Engineer (Outfits)

Machine Learning Engineer

Machine Learning Engineer

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.

ENGINEERING - GAMESWhat 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

Epic Games is looking for a Machine Learning Ops Engineer to support our team of Machine Learning engineers building solutions for internal use cases, such as classifiers for content moderation and security, semantic search, chatbots, etc. Your focus will be building reliable infrastructure for training, validating, serving, and monitoring our ML models at scale. This is an incredible opportunity to create a fun and safe environment for millions of players and make a positive impact on the Epic ecosystem.

In this role, you will

  • Work directly with our ML engineering team to improve codebase architecture, performance, observability and scale.
  • Operationalize proof of concept models into high availability production services, hosted on Amazon EKS, with a focus on factors such as latency, throughput and scalability.
  • Build and optimize CI/CD pipelines to enable a team of 20+ engineers to ship ML models at scale, quickly and safely.
  • Work with key stakeholders to identify technical debt and migrate legacy systems to the latest tools and platforms within Epic.

What we're looking for

  • Experience with engineering, data analytics, and machine learning.
  • Experience in building & maintaining technology used in ML development, with a focus on Python as the programming language.
  • Experience in building and maintaining infrastructure for training and deployment of large-scale ML/DL models that scale across clusters with CPU/GPU machines.
  • Experience in any of the following technologies and techniques is a plus: Pytorch, Torchserve, ONNX, Model quantization, TensorRT, OpenVINO, NVIDIA Triton.
  • Fluency in Unix/Linux tooling, shell scripting and operating systems internal is a plus.
  • Excellent communication and interpersonal skills.
  • BS/BA degree or equivalent work experience.

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 spans across 25 countries with 46 studios and 4,500+ employees globally. For over 25 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) Policyhere.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.