We are seeking an exceptional Head of Machine Learning to build and lead the ML capability within a leading hedge fund.

This is a senior, high-impact role responsible for defining the firm's machine learning strategy, building a world-class research team, and applying cutting-edge ML techniques to complex problems across systematic investing and financial markets.

We are open to outstanding individuals from hedge funds, investment banks, quantitative trading firms, leading technology companies and AI research organisations. Prior financial markets experience is advantageous but not essential for candidates with exceptional ML expertise.

• Define and lead the firm's overall machine learning research strategy.
• Build, hire and develop a high-calibre team of ML researchers and engineers.
• Lead research across areas including deep learning, reinforcement learning, probabilistic modelling, time-series modelling and generative AI.
• Partner with quantitative researchers and investment teams to apply ML to alpha generation, forecasting, portfolio construction, risk and execution.
• Develop robust approaches for working with large, noisy and non-stationary financial datasets.
• Establish best practices around experimentation, model validation, reproducibility and deployment.
• Identify emerging ML techniques with the potential to create differentiated investment capabilities.
• Work closely with engineering teams to develop scalable research and production infrastructure.
• Remain closely involved in technical and research direction while providing strategic leadership to the wider organisation.

The successful individual will bring:

• Deep expertise in machine learning, AI and statistical modelling.
• A track record of leading high-calibre researchers, scientists or engineers.
• Strong knowledge of modern ML techniques and their real-world application.
• Experience taking complex research ideas from hypothesis through experimentation and implementation.
• Strong programming skills, ideally with Python and modern ML frameworks such as PyTorch or JAX.
• Experience working with large-scale and complex datasets.
• Strong understanding of statistical validation, experimental design and model generalisation.
• The ability to combine technical depth with strategic leadership.

Candidates could come from:

• Systematic or multi-strategy hedge funds
• Quantitative trading or proprietary trading firms
• Investment banks
• Leading technology companies
• AI research organisations
• Advanced academic research environments

For candidates from finance, experience applying ML to systematic investing, quantitative research or trading would be particularly relevant.

For candidates coming from technology or AI research, previous financial experience is not essential where there is exceptional technical depth and an interest in applying ML to challenging quantitative problems.

A strong academic background in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering or a related quantitative discipline is preferred. A PhD is highly desirable but not essential.

Relevant expertise may include:

• Deep Learning
• Reinforcement Learning
• Probabilistic & Bayesian Modelling
• Time-Series & Sequence Modelling
• Representation Learning
• Generative AI / Foundation Models
• Optimisation
• PyTorch / JAX
• Python
• Large-scale ML systems

This is an opportunity to shape and build a machine learning function with significant strategic ownership. The successful candidate will have the resources and autonomy to hire exceptional talent, pursue ambitious research and directly influence how advanced ML is used across systematic investing.