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

Summary: The Principal Machine Learning Engineer will lead the technical direction for ADMET modeling within a drug discovery platform, focusing on machine learning applications in the life sciences sector. This role involves hands-on development of ML solutions, collaboration with cross-functional teams, and mentoring engineers and researchers. The position is fully remote and offers a significant influence over technical strategy without direct people management responsibilities. The contract length is between 6 to 12 months, with a competitive daily rate.

Key Responsibilities:

• Lead the design and implementation of ML solutions for ADMET using advanced 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 align 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.

Key Skills:

• 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 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.

Salary (Rate): 1200

City: undetermined

Country: United Kingdom

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT