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About the Role

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 bear across our research areas to transform the drug discovery world. Working in a highly creative, fast-paced and interdisciplinary environment, you will partner with leading research scientists and engineers to conceive, design, and develop cutting edge LLM applications that help to unlock new modelling capabilities and predictive power critical to the organisation’s success. You will draw upon your existing deep understanding and experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Responsibilities

Contribute to core research in machine learning by pushing the boundaries of Large Language Models in their application to the world of drug discovery.
Develop and refine LLM-driven approaches for multiple use cases across our research areas, using your extensive knowledge of the field to modify and apply models and explore their capabilities when applied to complex biological and medical challenges.
Identify and create novel ML techniques and the required data to train and apply models.
Analyse and tune experimental results to inform future experimental directions.
Implement and scale training and inference engineering frameworks.
Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
Suggest and engage in team collaborations to meet ambitious research goals.
Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
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.
Cultivate a diverse and inclusive research culture.

Requirements

PhD or equivalent practical experience in a technical field.
Highly specialized LLM builder with a passion for, and strong experience in, applying LLMs to novel problem spaces.
Deep understanding and experience of model architectures, training methods, and techniques for application of LLMs, including deployment for bespoke use cases and applications, established experience in post-training, reasoning, test-time scaling, tool-use, alignment, agents, LLM research, as well as reinforcement learning and fine-tuning.
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.
Strong knowledge of LLM landscape today, and likely developments for the near future.
Experience working with real-world datasets.
PhD in machine learning or computer science.
Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
A strong background in biology or medicine, enabling you to bridge the gap between advanced AI capabilities and complex scientific problems in drug discovery.
Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics), and with real world biological or chemical datasets and biological or chemistry software.
Experience in computational chemistry, bioinformatics, or related fields would be highly beneficial, along with a track record of applying AI to real-world scientific challenges.
Experience with multi-parameter optimization.
Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

Skills

Large Language Models (LLMs)
Machine Learning
Model Architectures
Training Methods
LLM Deployment
Post-training techniques
Reasoning
Test-time scaling
Tool-use
Alignment
Agents
LLM Research
Reinforcement Learning
Fine-tuning
Linear Algebra
Calculus
Statistics
JAX
PyTorch
TensorFlow
NumPy
SciPy
Pandas
Computational Biology
Computational Chemistry
Bioinformatics
Multi-parameter optimization
Large scale deep learning
Generative models
Graph neural networks
Deep learning for drug discovery
Deep learning for computer vision
3D graphics/robotics
Real-world applied RL

Location

Remote
Hybrid

Work Type

Hybrid

Experience Level

Research Scientist
Technical Mentorship
People Management

Education Level

PhD or equivalent practical experience in a technical field
PhD in machine learning or computer science

About the Company

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease.
The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery.
Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture.
The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you.
Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed.
Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases.
We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.
Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.

Equal 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 do not hesitate to let us know.