Principal Machine Learning Engineer, ADMET | Pharma/BioTech | Series A - Drug discovery B2B Pla[...]

Owen Thomas | Pending B Corp™; United Kingdom; Remote; GBP 125,000 - 150,000; Full time

Job summary

An innovative firm in the life sciences sector is on the lookout for a Principal Machine Learning Engineer to spearhead ADMET modeling in drug discovery. This fully remote role offers the chance to lead cutting-edge ML projects, collaborate with cross-functional teams, and mentor fellow engineers. With a focus on using advanced techniques like graph neural networks and transformers, you will play a pivotal role in shaping the future of drug discovery. If you are passionate about leveraging machine learning to make a real impact in healthcare, this opportunity is perfect for you.

Qualifications

• Lead technical direction for ADMET modeling in drug discovery.
• Mentor engineers and researchers in ML architecture and strategy.
• Collaborate on real-world drug discovery needs.

Responsibilities

• Design and implement ML solutions using advanced techniques.
• Build scalable production-grade ML pipelines.
• Contribute to scientific publications and open-source software.

Skills

Machine Learning

Computational Biology

Graph Neural Networks

Transformers

PyTorch

MLOps

Data Privacy

Statistical Analysis

Education

PhD in Machine Learning

Equivalent Experience

Tools

Docker

Kubernetes

Cloud Environments

Job description

Principal Machine Learning Engineer, ADMET | Pharma/BioTech | Series A - Drug discovery B2B Platform | Fully Remote, EU | £ 700-1,200 per day, Outside IR35 | 6-12 months Contract Length

Principal Machine Learning Engineer, ADMET | Pharma/BioTech | Series A - Drug discovery B2B Platform | Fully Remote, EU | £ 700-1,200 per day, Outside IR35 | 6-12 months Contract Length

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Principal Machine Learning Engineer, ADMET | Pharma/BioTech | Series A - Drug discovery B2B Platform | Fully Remote, EU | £ 700-1,200 per day, Outside IR35 | 6-12 months Contract Length

The Client:

A mission-driven technology company operating in the life sciences domain is seeking a Principal Machine Learning 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'll be the technical authority on ML architecture, experimentation, and strategy, collaborating closely with leadership and mentoring other engineers and researchers. While this is not a people management position, it offers significant influence over technical direction.

Responsibilities for the Principal Machine Learning Engineer, ADMET | Pharma/BioTech expertise | Series A - Drug discovery B2B Platform | Fully Remote, EU || Fully Remote, EU | £ 700-1,200 per day, Outside IR35

• Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers.
• 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.
• Build and maintain scalable, production-grade ML pipelines for training, inference, and deployment.
• Collaborate cross-functionally to ensure ML efforts are aligned with real-world drug discovery needs.
• Mentor team members in designing and executing complex modeling projects in structural biology.
• Contribute to strategic decisions regarding ML infrastructure, model architecture, and deployment processes.
• Author or contribute to scientific publications or open-source software where appropriate.

Expected Milestones

• By Month 3: Own an ADMET modeling stream and deliver a roadmap with a structured experimentation plan tailored to a key use case.
• By Month 12: Lead multiple ADMET ML initiatives, showing measurable performance improvements and tangible real-world outcomes. Serve as a strategic technical voice within the team.

Experience needed for the Principal Machine Learning Engineer, ADMET | Pharma/BioTech expertise | Series A - Drug discovery B2B Platform | Fully Remote, EU || Fully Remote, EU | £ 700-1,200 per day, Outside IR35

• A PhD (or equivalent experience) in machine learning, computational biology, computational chemistry, or cheminformatics.
• Strong track record applying ML to real-world drug discovery or pharmaceutical R&D problems.
• Deep experience building and deploying ADMET-focused models using graph neural networks (e.g., ChemProp) and transformer architectures.
• Proficiency with PyTorch or PyTorch Lightning and experience in designing large-scale model training workflows.
• Advanced understanding of assay protocols and methods for harmonizing heterogeneous ADMET datasets.
• Proven ability to deliver ML systems at scale, including distributed GPU training, CI/CD, model versioning, and deployment.
• Comfort working with modern MLOps tooling, including Docker, Kubernetes, cloud environments, and orchestration platforms.
• Strategic thinking with the ability to deconstruct complex modeling goals and drive them forward independently.
• Clear understanding of the role of ADMET models within drug discovery workflows and their impact on decision-making.

If interested in the Principal Machine Learning Engineer, ADMET | Pharma/BioTech | Series A - Drug discovery B2B Platform | Fully Remote, EU | £ 700-1,200 per day, Outside IR35 | 6-12 months Contract Length, please apply here with your CV, and we will get back if it's off interest to the client! :)

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Engineering and Information Technology

• Industries

  Public Health, Hospitals and Health Care, and Data Infrastructure and Analytics

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