Job Title: Machine Learning Engineer (all levels) Location: London (Hybrid)
We’re working with a well-funded technology company that is leading the way in revolutionising how drug treatments are discovered, tested, and developed through a computational approach. With a growing presence worldwide, they’re expanding their UK-based AI & Data team. They are building a world-class team of talented individuals passionate about innovation, pushing boundaries and working in a collaborative environment.
As a key member of the ML team, you will design and deploy clean, highly scalable algorithms and apply your expansive knowledge of recent, topical research domains to design novel solutions.
Ideally, you will come from an academic background, at minimum masters level but a PhD is preferred within computer science, operational research, computational biology, bioinformatics etc
Design, train, and optimise machine learning models for drug discovery applications, including compound screening, target identification, and lead optimisation.
Apply state-of-the-art techniques such as deep learning, reinforcement learning, and generative models to solve complex biological and chemical problems.
Work closely with computational chemists, biologists, and data scientists to define project goals and align machine learning strategies with scientific objectives.
Communicate complex ML concepts and results to non-technical stakeholders in a clear and concise manner.
Curate, preprocess and manage large-scale biological, chemical, and omics datasets.
Explore and identify insights from diverse data sources to inform model development and validation.
Industry-leading salary compensation DOE
An opportunity to work on projects that will make a difference in the world, all projects are multi-decade programs that are orientated to improve society and people’s lives
A rare opportunity to shape and lead the AI Capability team from the ground up
State-of-the-art resources, enabling you to push the boundaries of AI research and development quickly and ethically