Quantitative Researcher - Machine Learning

Salary: £62,000 - 102,000 per year

Requirements:

• PhD or exceptional MSc in Machine Learning, Computer Science, or a related field
• Deep theoretical and practical knowledge of core machine learning algorithms
• Comfortable experimenting with model architectures, feature engineering, and hyperparameter tuning to produce high-performance, resilient models
• Proven experience taking machine learning models from research to live production
• Deep understanding of modern machine learning algorithms, including transformer-based architectures and other state-of-the-art frameworks
• Experience applying machine learning models in financial markets is desirable, though strong candidates from tech, startups, or academia will also be considered

Responsibilities:

• Research, design, and deploy robust machine learning models
• Build and maintain scalable, production-level machine learning pipelines
• Extract signals from large, noisy, real-world datasets
• Apply advanced machine learning techniques to a wide range of forecasting challenges
• Deploy machine learning solutions in production while working with high-dimensional, noisy, structured and unstructured datasets

Technologies:

• Machine Learning

More:

We are DRW, a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, and we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into real estate, venture capital, and cryptoassets. We operate with respect, curiosity and open minds, and we look for people who share our belief that its not just what we do that matters, but how we do it. We are a place of high expectations, integrity, innovation and a willingness to challenge consensus.

last updated 36 week of 2026