AI Engineer, ML, NLP, Drug Discovery, Large Language Models
West London - office based 4 days per week
£65-87K + benefits
A stunning opportunity to join a company at the forefront of the AI-driven drug discovery revolution. We’re looking for MSc/PhD level Artificial Intelligence / Machine Learning experts to contribute to a transformational change in the way drug discovery is done with a high growth, fast-paced biotechnology company.
The AI/ML Engineer / Principal Scientist will specialise in AI applications and Large Language Models with particular focus on Life Sciences.
We're seeking talented Engineers and Scientists to join a stunning, world class, team embarking on a ground breaking project to develop and implement AI-driven innovations, supporting the implementation of next generation computational drug discovery and siRNA platforms.
You will need:
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MSc/PhD and ideally post-doctoral or similar experience, in AI/Machine Learning, Textual Analysis/Natural Language Processing and Transformer technology/Large Language Models
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Network Science and modern statistical methods would be a plus
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Proven track record of contributions to large AI domain software and data engineering projects relevant to the life sciences, ideally in drug discovery, preferably in a biotech start-up environment
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Good knowledge of cloud computing environments is essential with a preference for AWS
A spread of knowledge in several of the following will be advantageous:
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AI/ML approaches to problems in the Life Sciences
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NLP and Large Language Models
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Engineering and data solutions to support bioinformatic workflow design and development, with a focus on ML/AI applications
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An understanding of data management techniques for large-scale scientific data sets
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Programming skills in Java, C/C++, R or Python
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SOA NLP APIs and Machine Learning / Deep Learning frameworks
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Experience of translating user requirements into workflow designs/specifications
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Experience building and optimising data processing pipelines e.g. Nextflow/Nextflow Tower, SQL/NoSQL
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Experience with graph databases is highly desirable
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Version control, CI/CD, DevOps, and DataOps
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Cloud native technologies and approaches such as Docker and Kubernetes
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Experience of UX/UI design and deployment an advantage
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Ability to work well in a team and a willingness to 'go the extra mile’ to achieve joint goals
Some of the wider benefits:
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BUPA for self + partner/family
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Discretionary bonus
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10% employer pension contribution
AI Engineer | Senior AI Engineer | Principal Scientist | Senior Scientist | Senior Machine Learning Engineer