Machine Learning Engineer
King's Cross, Greater London, United Kingdom • Posted June 03, 2026
Job Type:
Full-time
Location:
King's Cross, Greater London
Posted:
June 03, 2026
Category:
other-general
Application Deadline:
July 13, 2026
Role Description
ROLE OVERVIEW:
We are currently looking for a Machine Learning Engineer to join a leading research organisation based in London. As Machine Learning Engineer, you will be responsible for advancing data-processing, model-building, and deployment capabilities for a pioneering research organisation.
KEY DUTIES AND RESPONSIBILITIES:
Your duties as the Machine Learning Engineer will be varied; however, the key duties and responsibilities are as follows:
1. Develop deep-learning pipelines for nuclear magnetic resonance (NMR) data and innovative machine learning approaches to elucidate and quantify interactions between small molecules and intrinsically disordered proteins.
2. Enhance the usability of built models by implementing automated, streamlined, and efficient software solutions in line with best practices, and build model-deployment and job-launching systems for internal and external use.
3. Collaborate closely with other computatio...
We are currently looking for a Machine Learning Engineer to join a leading research organisation based in London. As Machine Learning Engineer, you will be responsible for advancing data-processing, model-building, and deployment capabilities for a pioneering research organisation.
KEY DUTIES AND RESPONSIBILITIES:
Your duties as the Machine Learning Engineer will be varied; however, the key duties and responsibilities are as follows:
1. Develop deep-learning pipelines for nuclear magnetic resonance (NMR) data and innovative machine learning approaches to elucidate and quantify interactions between small molecules and intrinsically disordered proteins.
2. Enhance the usability of built models by implementing automated, streamlined, and efficient software solutions in line with best practices, and build model-deployment and job-launching systems for internal and external use.
3. Collaborate closely with other computatio...
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