Salary: £250-300k base
Summary
Highly skilled ML Researcher wanted for a leading global market maker to join one of their trading teams. This role offers the opportunity to join a firm-wide project, scaling up the alpha deep learning models, and leveraging innovative ideas and petabyte-scale data into models with an immediate impact on trading.
In this role, you will own the full research lifecycle end-to-end, iterate quickly and operate with high levels of resources and support in a flat, no-bureaucracy trading firm. Crucially, you’ll discover alpha in high-dimensional data with deep learning, time-series and representation learning, translating insights into executable strategies.
The successful candidate will have large-scale deep learning experience, and have communication and collaboration skills that are second to none, capable of fostering effective teamwork.
Skills and Experience Required
- Advanced training & strong research track record in statistics, ML, AI, or similar
- Deep-level knowledge of cutting-edge large-scale models and their training/design
- Demonstrated ability of taking ML ideas from theory to measurable impact
- Python fluency (NumPy, PyTorch) and experience writing clean, modular, performant code for large-scale experiments
- Hands-on modern ML experience (sequence models/transformers, representation learning, regularization, cross-validation, causal/robust inference)
- Masters/PhD in mathematics, statistics, physics, computer science, or similar highly quantitative field
NB: Please don’t apply if you’re a fresh graduate.
Rewards and Incentives
- Hugely collaborative environment between teams, not siloed like other firms
- Competitive compensation: truly flat structure; feel valued for your input and be rewarded for great ideas
- Genuine once-in-a-generation opportunity to have an impact
- Work with the latest technologies on complex problems
Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.