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# Senior ML Engineer

- **Company:** Epic Games, Inc.
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £57,656.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Computer Vision, Python (Programming Language), Machine Learning, NumPy, SciPy, Reinforcement Learning, Pytorch, Deep Learning, Scikit Learn, Information Technology, Machine Learning Operations, Unsupervised Learning
- **Published:** July 18, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5806143701

## About the Role

* PhD in Computer Science, Mathematics or related field, 5+ years of relevant industry experience
 * Proven track record creating innovative solutions for problems in Computer Vision and deploying them as production-level systems in industrial environments
 * Expert, hands-on knowledge of:
 + Deep learning techniques for supervised, semi-supervised and unsupervised learning
 + Reinforcement learning, imitation learning, and related frameworks
 + Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)
 * Experience with working collaboratively with other developers, following a flexible/agile/lean approach
 * Desirable:
 + Experience with architecting, scaling, securing and operating ML systems in the cloud (ideally AWS) at medium to large scale
 + Experience with 3D Vision/Graphics

## Description

You will work with our team of engineers at the intersection of vision, language and machine learning to create state-of-the-art models for agentic vision tools. You will be responsible for the design, implementation and deployment of production-ready computer vision models that support game developers in our ecosystem (including scene generation and trained bots/agents), as well as agents for automated content verification (e.g. gameplay behavior).
In this role, you will

 * Create and deliver production-ready, scalable and high-quality deep-learning models and associated algorithms for computer vision problems
 * Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap
 * Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones


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