Research Scientist (Applied LLMs), London London

Isomorphic Labs is a company focused on applying frontier AI to accelerate drug discovery and help solve diseases.

As a Research Scientist focused on the application of Large Language Models (LLMs), you will play an exciting role in bringing cutting‑edge technologies to our research areas to transform the drug discovery world. You will work in a highly creative, fast‑paced interdisciplinary environment, partnering with leading research scientists and engineers to conceive, design, and develop LLM applications that unlock new modelling capabilities. Depending on your experience, you may partner with existing research teams, create and lead standalone projects, and provide technical mentorship and people management for others in the ML community.

What you will do:

• Contribute to core research in machine learning by pushing the boundaries of LLMs in drug discovery.
• Develop and refine LLM‑driven approaches for multiple use cases across our research areas.
• Identify and create novel ML techniques and required data to train and apply models.
• Analyse and tune experimental results to inform future directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings clearly and efficiently to other ML scientists and domain experts.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.

Based on your experience:

• Provide technical mentorship and guidance to the ML research community, advising on projects and shaping our research roadmap.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high‑priority modelling problems.

Skills and qualifications:

Essential:

• PhD or equivalent practical experience in a technical field.
• Highly specialized LLM builder with passion for applying LLMs to novel problem spaces.
• Deep understanding of model architectures, training methods, and techniques for applying LLMs, including deployment, post‑training, reasoning, test‑time scaling, tool‑use, alignment, agents, and reinforcement learning.
• Strong knowledge of linear algebra, calculus, and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• Project supervision, leadership, or management experience (depending on your experience).
• Strong knowledge of the LLM landscape today and likely developments for the near future.
• Experience working with real‑world datasets.

Nice to have:

• PhD in machine learning or computer science.
• Post‑doctoral or similar research experience with a proven track record of publications or contributions to machine learning codebases.
• Strong background in biology or medicine to bridge AI capabilities with complex scientific problems in drug discovery.
• Experience working in a scientific environment across disciplines, with biological or chemical datasets and software.
• Experience in computational chemistry, bioinformatics, or related fields, and a track record of applying AI to real‑world scientific challenges.
• Experience with multi‑parameter optimization.
• Experience in large‑scale deep learning, generative models, graph neural networks, deep learning for drug discovery, computer vision, 3D graphics/robotics, real‑world applied reinforcement learning.

Hybrid working:

We follow a hybrid model and require you to be in the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on your team).

Equal Employment Opportunity:

We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please let us know.