Role overview
Welcome to Imperial, a global top ten university where scientific imagination leads to world-changing impact.
Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world’s toughest challenges. Whatever your role, your contribution will have a lasting impact.
As a member of our vibrant community of 22,000 students and 8,000 staff, you’ll collaborate with passionate minds across nine London campuses and a global network.
This is your chance to help shape the future. We hope you’ll join us at Imperial College London.
What you'll work on
Specifically, you will:
- Design, build, and maintain robust research software systems supporting large-scale probabilistic experiments on generative AI models.
- Lead the development of end-to-end computational pipelines, integrating model inference, sampling, verification, data aggregation, and statistical analysis.
- Engineer scalable and reliable workflows for running experiments on cloud and on-premise compute (e.g. AWS, GPUs, batch systems).
- Ensure reproducibility, version control, and auditability of research code, data artefacts, and experimental results.
- Work with researchers to translate novel statistical and machine-learning ideas into efficient, maintainable, production-quality research code.
- Advise on software architecture, performance optimisation, and technical risk, particularly for long-running or high-variance computational workloads.
- Contribute to open-source releases, documentation, and best-practice software engineering within the research group.
- Mentor junior researchers and developers in research software engineering practices.
- Support the preparation of technical reports, demonstrations, and research outputs for funders, stakeholders, and the wider research community.
What we're looking for
You will be an experienced research software engineer with strong technical judgement and a collaborative mindset.
We are particularly interested in candidates who have:
- Significant professional experience as a Research Software Engineer, Machine Learning Engineer, Software Engineer, or similar technical role in a research-intensive environment.
- Strong programming skills in Python and associated deep learning Frameworks, with experience in machine learning, or data-intensive systems.
- Experience designing and maintaining large, complex codebases used by multiple researchers or teams.
- Experience with cloud computing or HPC environments, including workflow orchestration and resource management.
- A strong commitment to software quality, testing, documentation, and reproducibility.
- The ability to work closely with researchers, understand evolving research needs, and translate them into robust technical solutions.
- Excellent communication skills and the ability to explain technical concepts clearly to non-software specialists.
Experience with probabilistic modelling, or large language models is desirable but not essential.