Machine Learning Scientist – Turing Team
London
About Relation
Relation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure.
This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting-edge ML capabilities with GSK’s deep expertise in drug discovery, this partnership underscores our commitment to pioneering science and delivering impactful therapies to patients.
We are rapidly scaling our technology and discovery teams, offering a unique opportunity to join one of the most innovative TechBio companies. Be part of our dynamic, interdisciplinary teams, collaborating closely to redefine the boundaries of possibility in drug discovery. Our state-of-the-art wet and dry laboratories, located in the heart of London, provide an exceptional environment to foster interdisciplinarity and turn groundbreaking ideas into impactful therapies for patients.
We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. We cultivate innovation through collaboration, empowering every team member to do their best work and reach their highest potential.
By joining Relation, you will become part of an exceptionally talented team with extraordinary leverage to advance the field of drug discovery. Your work will shape our culture, strategic direction, and, most importantly, impact patients’ lives.
Opportunity
Join the Turing team as a Machine Learning Scientist, where you will develop and apply advanced ML methods, with a strong emphasis on large language models (LLMs), reinforcement learning (RL), and multi-agent (agentic) systems. This role is ideal for a technically skilled ML scientist who is excited by the challenge of building intelligent agents that reason, act, and collaborate to solve complex biological problems.
The team you will join
The Turing team focuses on leveraging advanced ML approaches—LLMs, multi-agent reasoning systems, reinforcement learning, and modern representation learning—to transform how we understand biology and accelerate therapeutic discovery. We work across complex and incomplete heterogeneous data, designing agents and models that can reason, plan, and interface with experimental systems.
Your Responsibilities
- Design and implement ML systems using LLMs, RL, and multi-agent reasoning for drug discovery applications.
- Develop scalable workflows that allow agents to interact with biological data and external tools, enabling decision-making and hypothesis generation at scale.
- Collaborate with interdisciplinary teams (wet lab scientists, data scientists, engineers) to translate ML solutions into actionable insights for target discovery and validation.
- Apply best practices in modern ML engineering, ensuring reproducibility, scalability, and maintainability.
- Contribute to the broader ML research community through publications, workshops, and open-source code contributions.
You have
- PhD or Msc with relevant industry experience in Computer Science, Machine Learning, or a related field (or equivalent industry experience).
- Hands-on experience with LLMs (training, fine-tuning, evaluation, or deployment).
- Familiarity with reinforcement learning (e.g. policy optimisation, RLHF, actor-critic).
- Exposure to multi-agent or agentic ML systems (decision-making agents, tool-using LLMs, orchestration frameworks).
- Proficiency in Python and ML frameworks such as PyTorch or JAX.
- Strong software engineering practices (version control, testing, modular code, cloud environments).
Bonus if you have
- Experience applying ML to biological or healthcare data.
- Evidence of creativity in combining methods across ML sub-fields (LLMs, RL, graph methods, etc).
Personally, you are
- A strong problem solver who thrives on ambiguity and complexity.
- Team-oriented, enjoying close collaboration in small, fast-moving groups.
- Curious, motivated, and hungry to learn.
- Passionate about making a real impact for patients.
Join us in this exciting role, where your contributions will directly advance our understanding of human biology and accelerate the discovery of transformative medicines. The patient is waiting.
Relation is a committed equal opportunities employer.
