We have partnered with an end-to-end biotech company that is developing transformational medicines, with technology at its core. The company’s ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. It leverages single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure.

This year, the company embarked on a dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing its internal osteoporosis programme. By combining cutting-edge ML capabilities with GSK’s deep expertise in drug discovery, the partnership underscores the company’s commitment to pioneering science and delivering impactful therapies to patients.

The company is rapidly scaling its technology and discovery teams, creating a unique opportunity to join one of the most innovative TechBio organisations. Based in central London, its state-of-the-art wet and dry laboratories provide an exceptional environment where interdisciplinary collaboration thrives. It is pushing the boundaries of drug discovery and transforming groundbreaking science into impactful therapies for patients.

The company believes that innovation flourishes through diversity and collaboration. As an equal opportunities employer, it is committed to building inclusive teams where everyone can contribute their unique perspectives and thrive. Individuals from all backgrounds are encouraged to apply.

The Opportunity

The company is seeking a Research Engineer to join its Machine Learning group to drive the development, deployment, and scaling of ML and computational systems across the organisation. This role sits at the intersection of research and engineering, improving research workflows, supporting rapid experimentation, and enabling teams to push the limits of modern ML.

The Research Engineer will collaborate with machine learning scientists, data scientists, platform engineers, and other domain experts across the organisation. Depending on priorities, the engineer may work within a specific ML team or operate in a cross-functional capacity.

Based at the company’s wet/dry lab and headquarters in central London, the role involves working with large datasets, complex models, and high-performance compute. The engineer will strengthen training and inference pipelines, improve software foundations, and optimise the hybrid on-prem/cloud environment, including dedicated DGX clusters and collaborations with partners like NVIDIA.

Responsibilities

• Work with interdisciplinary teams to solve challenges across data engineering, ML engineering, and software engineering
• Build and improve data processing, transformation, and loading systems to support model training and inference at scale
• Develop and maintain high-quality research and production codebases to enable rapid, reproducible experimentation
• Advance software engineering practices by optimising systems, streamlining pipelines, and improving robustness across workflows

Education & Experience

• BSc/MSc/PhD in Computer Science, Machine Learning, Engineering, or related field
• 2+ years of industry experience

Core Skills

• Solid understanding of algorithms, data structures, and computational complexity
• Proficiency in Python with clean, maintainable coding practices
• Familiarity with PyTorch and common scientific Python libraries

Machine Learning Expertise

• Solid understanding of ML fundamentals and modern deep learning
• Experience training, evaluating, and iterating on models

Infrastructure

• Familiarity with AWS or GCP, Docker, Kubernetes, and CI/CD
• Familiarity with orchestration tools (Airflow, Prefect) and model-serving frameworks

Nice to Have

• Exposure to biology, bioinformatics, or machine learning for scientific domains

Personal Attributes

• Collaborative team player, able to communicate effectively with stakeholders from diverse backgrounds and technical abilities
• Passionate about science and making a real difference for patients
• Self-motivated, curious, and driven to succeed
• User-minded: considers how datasets and models will be used downstream
• Comfortable working independently and taking initiative

Why Join

• Work in a highly collaborative, interdisciplinary environment
• Access to state-of-the-art wet and dry lab facilities in central London
• Shape the systems and infrastructure that support cutting-edge ML research
• Contribute directly to advancing drug discovery and improving patient outcomes

The company is a committed equal opportunities employer and welcomes applicants from all backgrounds.