Machine Learning Team Lead – Foundation Models & Probabilistic AI London, UK (Hybrid) | £145,000+ & Significant Equity AI Drug Discovery Startup | Full-time
We’re an AI-native biotech company building foundation models for biology to transform how new medicines are discovered. By combining large-scale multimodal biological datasets with probabilistic machine learning and generative AI, we’re developing systems capable of predicting complex biological behaviour at unprecedented scale.
Our mission is to create general-purpose biological intelligence that accelerates therapeutic discovery across oncology, immunology, and rare diseases.
Backed by top-tier investors and leading scientific advisors, we’ve recently secured major funding to expand our ML platform and research capabilities globally.
We’re looking for a Machine Learning Team Lead to lead a high-performing team working on foundation models and probabilistic ML systems for drug discovery.
You’ll sit at the intersection of research and engineering – driving technical direction, mentoring senior engineers and researchers, and helping scale both our platform and team as we push toward state-of-the-art biological modelling.
This is a hands-on leadership role for someone excited by frontier AI, scientific impact, and building exceptional ML organisations.
Leading a team of ML engineers and applied researchers building large-scale foundation models for biological data Defining technical strategy across probabilistic modelling, representation learning, and generative AI systems Architecting scalable distributed training infrastructure for multi-billion parameter models Collaborating with computational biologists, cheminformaticians, and leadership on long-term research initiatives Mentoring and growing a world-class ML engineering team Helping shape hiring strategy and technical roadmap as the company scales
Proven experience leading ML engineering or applied research teams Strong background building and scaling deep learning systems in production Deep understanding of foundation model architectures and modern generative AI techniques Experience with probabilistic ML approaches such as Bayesian inference, latent variable models, or uncertainty-aware systems Strong software engineering and distributed systems experience Excellent communication and stakeholder management skills Experience in biotech, computational biology, or AI for science Publications or contributions in advanced ML research Experience scaling ML organisations in startup environments Lead one of the most technically ambitious AI teams in biotech Work on frontier AI problems with direct impact on human health Competitive compensation and meaningful equity package Collaborative culture built around scientific curiosity and engineering excellence…