Senior Quantitative Researcher, Deep Learning/AI

Senior Quantitative Researcher - AI / Deep Learning (Confidential)

About the opportunity

We are working with a highly successful quantitative investment firm on a confidential senior research mandate.

The firm is expanding a specialist research group focused on applying advanced machine learning and deep learning techniques to systematic trading. The team has a broad mandate, significant internal backing, and the infrastructure to take research from initial idea generation through to live deployment.

This is a research-led role, not an applied AI or tooling function. The focus is on developing predictive models and systematic strategies where machine learning is central to the investment process.

The role

You will work as a quantitative researcher on end-to-end strategy development, with a particular focus on deep learning, time series modelling, and signal generation.

You will be responsible for shaping research direction, building and testing models, evaluating live performance, and contributing directly to trading outcomes. The environment combines the pace and autonomy of a focused research team with the resources, data, and execution capabilities of an established platform.

What we’re looking for

We are interested in speaking with researchers who have:

* Several years of quantitative research experience within systematic trading, market making, or multi-strategy investment environments

* Strong depth in machine learning, neural networks, and time series forecasting

* Experience applying predictive modelling to alpha research, signal generation, or trading strategy development

* A track record of research that has been deployed into production or had direct commercial / P&L impact

* Strong programming ability, typically in Python, with PyTorch, JAX, TensorFlow, or similar frameworks

* An advanced degree in a quantitative discipline, ideally PhD-level, though this is not essential

Profiles of particular interest

We are especially interested in researchers who have:

* Worked in quantitative finance before moving into frontier AI, research labs, or major technology companies

* Built deep learning models for financial time series, alpha generation, or systematic trading

* Operated in environments where research ownership extends beyond modelling into live performance and iteration

Not a fit

This is unlikely to be the right opportunity for candidates whose experience is primarily:

* General AI research with no prior finance exposure

* LLM tooling, applied AI, or AI productivity use cases

* Quant roles where machine learning is only used as a secondary research aid rather than a core modelling approach

* Engineering-heavy ML roles without direct research ownership

Compensation

Compensation is highly competitive in the seven figure range for senior hires, depending on experience, track record, and seniority.

Process

The process will be handled discreetly. For candidates from directly relevant firms, an informal initial conversation can be arranged before entering a formal interview process.