Nearhuman
Machine Learning Researcher - Founding Team
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Machine Learning Researcher — Founding Team
Nearhuman · Bristol, UK · On-site
Nearhuman is hiring a Machine Learning Researcher to join our founding team and contribute to original AI research.
We’re looking for someone who wants to understand how models work—not just how to use them. Someone who can take a research idea, turn it into a working implementation, and design experiments that tell us whether it holds up.
This is a hands-on role combining mathematical understanding, research judgement and strong programming ability. You’ll work directly with the founder, helping shape research decisions and taking ownership of work from initial hypothesis to evaluated results.
The role
Your focus will be model-level research and development, rather than building applications around existing AI APIs.
You will:
- Develop and investigate research ideas. Turn open-ended questions about neural networks and learning into clear hypotheses and practical experiments.
- Build the implementations. Write and modify model components, training loops and evaluation pipelines in Python and PyTorch. Diagnose problems rather than treating the training process as a black box.
- Evaluate rigorously. Reproduce relevant results, establish credible baselines and run controlled comparisons and ablation studies. Distinguish meaningful improvements from noise, implementation errors or unfair comparisons.
- Make the work reproducible and useful. Maintain clear code, experiment records and technical notes. Explain what worked, what failed and what the evidence supports doing next.
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What we’re looking for
- Strong machine learning fundamentals. You understand neural networks, backpropagation, optimisation and training dynamics, supported by a solid foundation in linear algebra, probability and calculus.
- Research-level implementation skills. You can translate a mathematical description or research paper into working code, inspect intermediate behaviour and debug numerical or training issues.
- Evidence of independent research ability. You have investigated a substantive machine learning question through academic research, industry work, open-source contributions or a self-directed project.
- Sound judgement and ownership. You can make progress without a fully specified task, explain your technical choices and change direction when the evidence challenges your assumptions.
Experience modifying neural-network architectures or investigating learning methods is particularly relevant. Familiarity with GPU-based experimentation, profiling and efficient tensor operations would also be useful.
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A relevant PhD is welcome, but not required. Strong work and a clear understanding of your own results matter more than a particular qualification or publication count.
Working at Nearhuman
You’ll join a small team where your contribution will directly influence the research direction. The role involves building the tools, running the experiments and making decisions—not only proposing ideas.
There will be uncertainty, unsuccessful experiments and questions without established answers. We’re looking for someone who finds that work worthwhile and approaches it with curiosity and discipline.
This is an on-site position in Bristol, with close collaboration across the founding team.
How to apply
Apply with your CV and one or two examples of relevant work. These could be a paper, repository, technical report or a short, non-confidential account of a project.
For one example, briefly explain:
What question were you investigating? What did you personally implement? How did you test it, and what did you learn?
We’re interested in the quality of your thinking and the work behind the result—including experiments that did not support your original idea.
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