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# Machine Learning Engineeer - Remote

- **Company:** YO HR Consultancy
- **Location:** UK (Remote available)
- **Salary:** £208,000.0 - £312,000.0
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Command-Line Interface, Software Debugging, Python (Programming Language), Machine Learning, NumPy, Open Source Technology, Performance Tuning, SciPy, Pytorch, Numerical Computing, Information Technology, HuggingFace, Data Pipelines
- **Published:** September 20, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5891230736

## About the Role

We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python.

The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements.

This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow., * A master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.

 * Strong professional or research experience in machine learning.
 * Practical proficiency withPython and coding agents.

Relevant tools may include:

 * PyTorch
 * JAX
 * NumPy and SciPy
 * SGLang
 * vLLM
 * llama.cpp
 * Hugging Face Transformers
 * Hugging Face Tokenizers

Equivalent tools may also be considered when the candidate demonstrates directly relevant depth.

Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify.

## Description

* Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
 * Implement model components, data pipelines, evaluation systems, and numerical methods.
 * Build reproducible programmatic workflows using Python and command-line tools.


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