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# Machine Learning Research Scientist

- **Company:** THE OPPORTUNITY HUB UK LTD
- **Location:** Liverpool, United Kingdom
- **Experience:** Expert
- **Salary:** £65,000 - £91,500
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Python (Programming Language), Machine Learning, Tensorflow, Software Deployment, Pytorch, Deep Learning, Model Validation
- **Published:** November 4, 2026
- **Apply:** https://www.jobs.service.gov.uk/jobs/6aeada52e0e8b4d9c5072221/apply

## About the Role

A strong track record in applied machine learning research, ideally with published work or production deployments to show for it

Deep fluency in Python and at least one major deep learning framework (PyTorch or TensorFlow)

Comfort working with ambiguity. Startups rarely hand you a clean brief

The judgement to know when a research idea is worth three weeks and when it isn't worth three days

Clear written and verbal communication, especially when explaining technical tradeoffs to people outside the field

Experience mentoring or reviewing the work of less senior researchers

## Description

An exceptional opportunity for a senior Machine Learning Research Scientist to shape the future of AI & Technology in Liverpool.

Model performance plateaus the moment research stops talking to production, and most AI & Technology teams never fix that gap. This growing startup has built its product around closing it, with a small research function that gets heard at every level of the business. You'd join as Machine Learning Research Scientist at a stage where your decisions still carry real weight.

Here's what you'll be doing:

Design and run experiments that test new model architectures against real production constraints, not just benchmark scores

Translate research findings into deployable models, working closely with engineers to get them into production quickly

Own the evaluation framework for model quality, catching regressions before customers do

Read and assess emerging papers relevant to the company's roadmap, then decide what's worth building

Mentor junior researchers and engineers on experimental rigour and good ML practice

Present findings to non-technical stakeholders in language that actually lands