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Fixed-term: The funds for this post are available until 30 April 2026.

Artificial intelligence (AI) has the potential to become an engine for scientific discovery across disciplines. The Accelerate Programme for Scientific Discovery (https://acceleratescience.github.io/index.html) is a high-profile University initiative promoting the use of machine learning (ML) to tackle major scientific challenges. Working across disciplines and across the University, the Programme is:

• providing researchers with specialised training, equipping them with the skills they need to use ML and AI to power their research.

• pursuing an ambitious research agenda that applies ML to the scientific challenges of the 21st century.

• building a community of researchers working at the interface of machine learning and the sciences sharing knowledge and experiences that help advance the use of machine learning in the sciences.

Software development is a highly valuable resource that includes modelling, simulation and data-analysis. Generating well-designed software will in turn increase the scope, productivity, reliability, replicability and therefore openness of research. In pursuit of these goals, we are seeking an experienced Senior Machine Learning Engineer (SMLE) to lead the development of our software culture and manage the Programme's Software Engineering team.

The role-holder will lead software development activities that facilitate the application of ML for scientific discovery. By providing software engineering support, advising on the development of research projects and delivering training and mentoring to researchers across the University, the role-holder will create an environment in which researchers are empowered to build high-quality research software.

The SMLE will be responsible for the Programme's Machine Learning Engineering Clinic, which supports Cambridge University researchers to resolve engineering issues when implementing machine learning (https://acceleratescience.github.io/machine-learning-clinic). The role-holder will also contribute to teaching activities and details on our courses can be found in the further particulars.

Successful candidates will have:

• Experience of software engineering development processes commonly deployed in research and development. Examples could include the use of agile development techniques to respond to emerging research needs or use of open-source models to build an active community around a shared code resource.

• Sufficient breadth and depth of specialist knowledge in software engineering to develop research objectives, projects and proposals. This will include substantial knowledge and experience of scientific/numerical/data-intensive programming; expert knowledge of one or more of Fortran/C/C++/Python/R; and a broad range of software skills that can be applied to scientific software design.

• The ability to communicate technical concepts effectively and enthusiastically across disciplines and to audiences with a range of technical abilities.

• Organisational skills to work independently, developing and managing projects to agreed parameters.

• Experience of working in interdisciplinary teams.

• Experience of managing technical staff.

The post is offered on a full-time basis, but we are also interested in hearing from candidates that may wish to work part-time. If you have any questions about the role, please contact Jess Montgomery ([email protected])

The deadline for applications is 7 July. We anticipate holding interviews during w/c 17 July.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

To apply, please submit: A CV and publications list, a cover letter explaining how your experience relates to the core skills required for the role, a short summary (max. 1 page) setting out your view on "what role do you believe software engineering can play in building the Cambridge AI for science community?" and names of two referees who may be contacted during the application process.

Please quote reference NR37032 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.