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Senior Machine Learning Engineer, Accelerate Programme for Scientific Discovery (Fixed Term)

University of Cambridge - Department of Computer Science and Technology, West Cambridge

Location: Cambridge
Salary: £45,585 to £57,696
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 15th May 2024
Closes: 13th June 2024
Job Ref: NR41680

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.

Accelerate Science:

  • provides researchers with specialised training in AI techniques, equipping them with the skills they need to use machine learning and AI to power their research.
  • pursues an ambitious research agenda that applies machine learning to the scientific challenges of the 21st century.
  • nurtures a community of researchers working at the interface of machine learning and the sciences.

Generating well-designed software will increase the scope, productivity, reliability, replicability and openness of research. In pursuit of these goals, we are seeking experienced Senior Machine Learning Engineers (SMLE) to lead the development of our software culture.

Role holders will facilitate the application of machine learning for scientific discovery across a range of projects and activities. By providing software engineering support, advising on the development of diverse research projects, and delivering training and mentoring to researchers across the University, successful candidates will help create an environment in which researchers from across domains are empowered to create and support high-quality research software. For example, Senior Machine Learning Engineers will collaborate with researchers and Accelerate's partners across Cambridge to develop research objectives, projects, and proposals, providing strategic advice for research software through routes including the AI Clinic (https://acceleratescience.github.io/machine-learning-clinic). The role-holder will also contribute to teaching activities, including training researchers from across disciplines in core concepts and practical applications of AI. They will act as evangelists for machine learning in science, helping create a community of researchers working on pressing scientific and societal challenges across the University.

We're looking for experienced machine learning engineers who have:

  • The specialist knowledge that will allow them to tackle challenges in machine learning development and deployment, including knowledge and experience of core methods in machine learning, data science, and programming.
  • A broad range of software skills that they can adapt to diverse challenges.
  • The ability to collaborate effectively with scientists from different domains.
  • The ability to work independently, with a high degree of self-motivation, including the organisational skills to manage projects.
  • Excellent communication skills, and the ability engage audiences with different levels of familiarity with technical concepts.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK. Please note that we provide the support of applying for the relevant visa (if required) and we reimburse the cost of the first visa.

To complete your application, please submit a CV and publication 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.  If you upload any documents which have not been requested, we will not be able to consider these as part of your application.

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

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