Join a fast-growing team at the forefront of AI-driven drug discovery in life sciences. Our client in San Francisco is using state-of-the-art machine learning to revolutionise how drugs are designed, optimised, and brought to market. As a Machine Learning Engineer, you’ll work on complex biological datasets, from cell imaging to molecular modelling, helping to build AI systems that directly guide scientists in designing safer, more effective treatments.

What you’ll do

• Develop and optimise deep learning models for toxicity prediction, molecular generation, and phenotypic analysis
• Work with petabyte-scale biological data, including gene expression, cell imaging, and metabolic profiling
• Contribute to multimodal models that integrate clinical, molecular, and experimental data
• Collaborate with experts across bioinformatics, chemistry, and AI infrastructure to deliver impactful solutions
• Build tools and pipelines that enable rapid experimentation and deployment in a production environment

About you

• Strong background in machine learning, with experience in deep learning architectures (e.g. GNNs, transformers)
• Skilled in Python and ML frameworks such as PyTorch or TensorFlow
• Experience working with large, noisy datasets, ideally in a scientific or biomedical context
• Passion for applying AI to real-world challenges in health, drug discovery, or biology
• Excited by interdisciplinary work and rapid innovation

This is a unique opportunity to apply your ML skills to problems that truly matter—reshaping the future of medicine with a world-class team at the leading edge of AI and biotech.