ML Research Engineer, London London

Isomorphic Labs Limited; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A cutting-edge AI research firm in Greater London seeks Research Engineers with expertise in machine learning to contribute to revolutionary advancements in drug design. The role involves developing state-of-the-art AI models, working closely with scientists to drive innovation and participating in a dynamic, collaborative environment. Strong programming background and proficiency in ML frameworks are essential. This opportunity offers the chance to impact the biopharmaceutical sector significantly.

Qualifications

• PhD in a technical subject with exposure to AI/ML, or BSc/MSc with 2+ years experience.
• Strong experience in software design and algorithms.
• Understanding of ML theory and applications.

Responsibilities

• Develop and optimise AI models and codebases.
• Run experiments to evaluate ML model performance.
• Collaborate with scientists to enhance AI model outputs.

Skills

Machine Learning

Software Engineering

AI Model Development

Deep Learning Frameworks

Statistical Analysis

Education

PhD in a technical subject

BSc or MSc with 2+ years ML experience

Tools

JAX

PyTorch

TensorFlow

Job description

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.

About Iso

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.

Research Engineering (Machine Learning), London or Lausanne

We are looking for Research Engineers with different levels of experience – Mid through to Senior, Staff, Principal or equivalent levels.

Your impact

This is an exciting opportunity for you to contribute to frontier research at the intersection of AI and drug design.

Working in a highly creative, iterative environment, you will be partnering with scientists and engineers to advance foundational models that will transform the biopharmaceutical world as we know it.

You will draw upon your existing engineering and Machine Learning experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

What you will do

• Translate research concepts into practical implementations by developing and optimising state‑of‑the‑art AI models, and building and maintaining robust codebases, data pipelines, and infrastructure for training and evaluation.
• Design, implement, and run experiments to evaluate the performance and robustness of ML models, using a full spectrum of state‑of‑the‑art machine learning methods. Evaluating, tuning, and maintaining AI/ML models (which includes collecting and preparing data as needed)

Evaluation & Inference

• Implement algorithms and software to analyse and evaluate the performance of AI models.
• Optimise performance of AI/ML models such as Diffusion models, Transformers, GNNs, leveraging a deep understanding of the AI/ML hardware+software stack
• Advise on how to bring AI/ML models to production and/or integrate them into product offerings, and monitor and refine their behaviour.
• Develop specialised tools/frameworks/infrastructure to aid in the work above.
• Work closely with research scientists and engineers, contributing to team discussions, sharing knowledge, and actively participating in code reviews to foster a collaborative environment.
• Proactively identify and address technical challenges, stay updated on the latest AI advancements, and focus on developing solutions that enable scaling our wider foundation and applied model platforms.
• Ability to execute on independent engineering projects and software development towards research goals.

Skills and Qualifications

• PhD in a technical subject with a major engineering component and exposure to AI/ML, or BSc, MSc and 2+ years of specific experience working on ML model development:
• Strong general engineering experience, as evidenced by exposure to one or more of:
• Software design / algorithms, especially for deep learning frameworks
• Modern ML frameworks such as JAX, PyTorch or TensorFlow
• Distributed systems and runtimes
• Large‑scale model training and serving infrastructure
• Experience in navigating complex research codebases
• Databases and data processing pipelines
• Numerical methods, simulation, optimisation
• Experience with the full ML research and development lifecycle.
• Strong understanding of ML theory and applications.
• Strong understanding of data structures and algorithms.

Nice to have

• Interest in chemistry and biology.
• Experience working with biomedical data.
• Knowledge of the pharmaceutical industry, ideally with a focus on drug discovery.

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.