Our compact, talent-dense team.

Professor of Machine Learning at Cambridge. Highly cited, and widely read at inference.vc. Led ML research at Twitter after Magic Pony's $150m acquisition.

Enterprise tech exec. Scaled products and businesses at $1b+ scale. EVP at Teads/Outbrain, exec at Unruly (acquired by News Corp). XP leading capital raises, an IPO and ~$1b acquisition.

Experienced HR leader, built and scaled high-velocity innovative teams and HR functions, previously Turbine AI and GE Healthcare. Economist by training, builder at heart.

Talent Acquisition leader with a track record building high-performing, highly technical teams internationally. Previously Arm and AWS, and a founder background.

PhD in Computer Science. Research focus includes continual learning and memory management, mechanisms of learning, agent sandboxing and evaluation.

Software engineer and computer scientist with a strong interest in designing and building robust large-scale distributed systems.

Engineer and entrepreneur, co-founder of MindOne and BitRaptors, with experience building products for high-growth companies including Skyscanner, Oda, and Trustpilot.

PhD in ML at Cambridge, DeepMind scholar. Out-of-distribution generalization of LLMs, with spotlight papers at NeurIPS and ICML. EGMO medalist.

IAIO gold medallist, two-time EGOI silver medallist, currently a final year student at Stephen Perse, Cambridge.

Theoretical computer science MSc (ETH Zurich) turned builder. Quant with Squarepoint, Stateless Election Technologies, and Morgan Stanley.

PhD in Machine Learning at Cambridge, previously at Apple MLR. LLM emergent behaviours, generalisation and data selection.

PhD in Machine Learning at Uppsala University. Focusing on robust machine learning and resource constraint optimization.

IOI silver medallist, starting a BA in Computer Science at Christ's College, Cambridge.

IMO & IOI Silver medallist beginning his second year of maths at Trinity College, Cambridge.

Assistant Professor at the University of Toronto. Co-creator of Anvil, working on formal verification for real-world, large-scale systems.