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# Machine Learning Engineer

- **Company:** Iconic Interactive
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Data Cleansing, Game Engine, Python (Programming Language), Machine Learning, Pytorch, Large Language Models, Information Technology, Build Tools, Unreal Engine
- **Published:** September 8, 2026
- **Apply:** https://startup.jobs/machine-learning-engineer-iconic-9947643

## About the Role

* Strong knowledge of Python
 * Experience writing models in PyTorch or JAX
 * A good understanding of how large language models work
 * Comfortable working along the whole ML pipeline: from data preparation to model design, training and evaluation, and shipping in products
 * Degree in Computer Science or a related field, or equivalent industry or personal experience (show us your personal projects!)

Nice to Have:

 * Experience building agent harnesses or user-facing systems based on LLMs
 * Experience shipping machine learning models on consumer devices or edge compute
 * Experience optimising, quantising or writing kernels for LLMs
 * Knowledge of C/C++, or experience with Unreal Engine, Unity or similar game engines
 * Experience with managing ML environments and hardware
 * Experience working with audio models or other multi-modal models.
 * An appreciation for game design and development principles

## Description

We're looking for an experienced Machine Learning engineer to join our team, focused on building custom, efficient models and integrations to power real-time interaction for the next generation of games and interactive experiences.

As part of a small, focused team, you'll have significant autonomy and end-to-end ownership over design and implementation. You'll work closely with artists, writers and designers as well as the rest of the engineering team to build systems that actually translate into creative & fun games.

What You'll Do:

 * Build, train and integrate ML models for real-time interactive experiences
 * Develop systems and applications powered by LLMs
 * Own projects across the ML pipeline, from experimentation through to production
 * Optimise models for performance, latency and efficiency
 * Work with engineering and creative teams to turn ML capabilities into compelling experiences


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