Principal Machine Learning Scientist | ADMET/Structural Biology | Series A - Drug discovery Platform | Fully Remote, EU | Base Salary Up to £160,000K, plus early equity+benefits in Leeds

The Client: A mission-driven technology company operating in the life sciences domain is seeking a Principal Scientist - hands-on with either ADMET or Structural Biology modelling, ML engineer to lead the technical direction for ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) modeling efforts within its drug discovery platform. The organisation enables collaborative model development across partner organisations while maintaining strict data privacy and ownership, using a federated data infrastructure.

In this hands-on, high-impact role, you’ll work at the intersection of machine learning, computational chemistry, and applied research to advance foundational model applications in drug discovery. You will be the technical authority on ML architecture, experimentation, and strategy, while focusing specifically on data security and privacy. You will also collaborate closely with leadership and mentor other engineers and researchers. While this is not a people management position, it offers significant influence over technical direction.

Responsibilities:

• Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers.
• Lead the research and implementation of data privacy within the models and establish privacy attack-surface assessment.
• Develop and extend models for specific applications, including data distillation, benchmarking, and evaluation.
• Define preprocessing and harmonization strategies for diverse assay datasets used in ADMET modeling.
• Author or contribute to scientific publications or open-source software where appropriate.

3 Month Plan:

• Develop a working understanding of the product, federated training setup, and key life-sciences modelling use cases.
• Reproduce and extend at least one existing modelling pipeline to establish a baseline privacy and attack-surface assessment.
• Contribute to privacy analysis for one or more active federated drug discovery programs as they transition from setup into live operation.

Experience needed:

• PhD in computational chemistry or equivalent.
• Drug discovery experience (5y+).
• Hands-on ADMET or Structural Biology modelling experience (broad scope).
• Hands-on experience building an ML based model on public and/or internal pharma datasets in the computational chemistry space.
• Strong understanding of OpenFold, AlphaFold, Boltz and co-folding.
• Confidence in building silico models.
• Excellent communicator and connecting stakeholders.
• Excellent planning capabilities for experimental planning and execution.
• Experience in working in consortium is a plus.

Remuneration:

• Up to £160,000 Base Salary.
• Attractive Stock Options.
• B2B & Full-time employee options.
• Flexible hours +/- 3 hours of CET time zone.

If you think you are a good match for the role, send us your CV and if we think you are a good match, we will give you a call!