Jobs

Machine Learning Engineer


Job details
  • The University of Edinburgh
  • Midlothian
  • 4 months ago
Applications closed

Grade UE07 - £39,347 - £46,974 per annum

College of Medicine & Veterinary Medicine - Clinical Sciences

Full time - 35 hours per week

Fixed term contract to 28 February 2027

The Opportunity:

Founded in 2024, the Learning Model of Life is a cross-college initiative of The University of Edinburgh. We are a constituent of the University’s Generative AI Lab (GAIL) and are supported by EPCC, the UK’s leading centre of Supercomputing and Data Science. 

We are seeking a dynamic and innovative Machine Learning Engineer to lead the development of advanced AI models. You'll be at the forefront of creating and deploying advanced tools that harness the power of NLP and generative AI to unlock new insights in biological sciences. This is a unique opportunity to have real impact by developing technologies that will drive the next wave of breakthroughs in genetics. You will work in a vibrant academic environment at the University of Edinburgh, surrounded by experts in biology, medicine, computing, and machine learning. You'll have freedom to innovate, support to grow, and the opportunity to contribute to research that will transform the future of healthcare and beyond.

This post is full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working. 

Your skills and attributes for success: 

Relevant university degree, in a relevant technical discipline (e.g., artificial intelligence, computer science, software engineering) or relevant post-degree professional experience (i.e. experience in a similar role). Strong Python development skills, with a good knowledge of existing packages for AI/NLP development. A very good knowledge of existing NLP techniques, LLMs and evaluation frameworks. Experience of training and/or fine-tuning custom AI/ML models. Evidence of having used git and associated tools (e.g. GitHub) for version control.

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