Quantitative Researcher - Machine Learning
DRWAbout the Role
The Machine Learning Researcher will have a deep understanding of the principles behind modern ML algorithms — including recent advances such as transformer-based architectures and other state-of-the-art frameworks — and the ability to turn that knowledge into high-impact, production-ready solutions.
The role involves applying advanced ML techniques to a wide range of forecasting challenges, building scalable ML pipelines, and deploying them in production, while working with high-dimensional, noisy, structured and unstructured datasets. Experience applying ML models in financial markets is desirable, but exceptional candidates with a strong ML background from tech, startups, or academia will also be considered.
- Research, design, and deploy robust ML models
- Build and maintain scalable, production-level ML pipelines
- Extract signals from large, noisy, real-world datasets
Requirements
- PhD (or exceptional MSc) in ML, Computer Science, or related field.
- Deep theoretical and practical knowledge of core ML algorithms, and comfortable experimenting with model architectures, feature engineering, and hyperparameter tuning to produce high-performance and resilient models.
- Proven experience taking ML models from research to live production.
- Deep understanding of the principles behind modern ML algorithms, including recent advances such as transformer-based architectures and other state-of-the-art frameworks, and the ability to turn that knowledge into high-impact, production-ready solutions.