Senior Machine Learning Researcher : Elite Quant Fund : £300-400k+

Hunter Bond; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Hunter Bond is seeking a Senior Machine Learning Researcher for a leading quantitative investment fund. The role focuses on advancing machine learning research applied to quantitative finance, with access to substantial computational and research resources.

The successful candidate will work on challenging problems at the intersection of ML, large-scale data, and finance, contributing to the fund's ML capabilities and research strategy.

Qualifications

• Strong academic background in machine learning, computer science, mathematics, physics or related quantitative discipline.
• Master's degree from a leading university or equivalent academic institution.
• Significant industry experience in machine learning research.

Responsibilities

• Define and pursue new research directions and open-ended questions independently.
• Develop and evaluate novel machine learning methodologies for financial data.

Skills

Diffusion models

Transformer architectures

Computer vision

Deep learning

Self-supervised learning

Large-scale model development

Novel neural networks

Education

Master's degree

Job description

A leading quantitative investment fund is seeking to appoint a Senior Machine Learning Researcher to join and further develop its Machine Learning Research function. The team focused on applying advanced machine learning research to quantitative investment and financial markets.

The successful candidate will have the opportunity to work on challenging, open-ended research problems at the intersection of machine learning, large-scale data and quantitative finance, with access to significant computational and research resources. Candidates should have a strong understanding of the underlying principles of modern machine learning and a demonstrated ability to conduct rigorous, independent research.

The team is particularly interested in researchers with strong expertise in one or more of the following areas:

• Diffusion models and generative modelling
• Transformer architectures and foundation models
• Computer vision and visual representation learning
• Deep learning
• Self-supervised and representation learning
• Large-scale model development and training
• Novel neural network architectures and modelling techniques

The preferred candidate will have experience in machine learning research, applied research or a closely related discipline. The fund places particular value on depth of industry research experience and demonstrated technical capability.

Candidates are expected to demonstrate:

• A strong academic background in machine learning, computer science, mathematics, physics or a related quantitative discipline
• A Master's degree from a leading university or equivalent academic institution
• Significant industry experience in machine learning research
• Demonstrable expertise in diffusion models, transformers, computer vision or related areas
• Strong mathematical and statistical foundations
• Experience developing, evaluating and implementing novel machine learning approaches
• The ability to formulate and investigate open-ended research questions independently
• A high level of technical proficiency and intellectual curiosity

The successful candidate will join a high-calibre research environment and will be expected to make a significant contribution to the development of the firm's machine learning capabilities.

There is substantial scope for the successful researcher to:

• Define and pursue new research directions
• Develop novel machine learning methodologies for application to financial data
• Collaborate closely with quantitative researchers and other machine learning specialists
• Access significant computational and research resources
• Contribute to the development of the firm's broader machine learning research strategy
• Build and lead a dedicated research team as the function expands