Techfellow Limited

Compensation

Full Description

[Up to c. $400k Comp Package | Hybrid Working] Role Overview We’re representing a leading proprietary trading firm in its search for Machine Learning Research Lead - an opportunity to lead the design, deployment, and evolution of cutting-edge ML systems that power high-performance trading across global markets. In this hands-on leadership role, you’ll build and guide a multidisciplinary research group focused on applying modern machine learning to price prediction, signal extraction, and strategy optimisation. You’ll shape the firm’s central ML research platform, collaborate closely with quantitative traders and software engineers, and champion the translation of research into production-grade systems. This is an opportunity for an innovative thinker who combines deep technical expertise with strong leadership instincts and a pragmatic understanding of real-world trading dynamics... Key Responsibilities • Set the research agenda and technical direction for ML initiatives supporting trading and strategy development across asset classes • Lead the design, training, and deployment of advanced models for predictive analytics, signal discovery, and execution optimisation • Drive the creation of a unified, scalable ML research environment - enabling experimentation, model comparison, and data curation across teams • Partner with quant researchers, traders, and technologists to translate market hypotheses into testable features and model frameworks • Oversee end-to-end data workflows, from acquisition and cleaning to feature generation for structured, semi-structured, and unstructured data • Evaluate emerging methodologies in deep learning, reinforcement learning, and representation learning, identifying opportunities for commercial impact • Establish best practices for reproducible research, experimentation pipelines, and ML infrastructure management • Mentor and grow a high-performing team of machine learning scientists and research engineers, fostering collaboration and intellectual curiosity • Contribute to the firm’s long-term strategy on data, model governance, and the integration of ML capabilities into trading systems What You’ll Bring... • PhD or Master’s in Computer Science, Applied Mathematics, Engineering, or a related quantitative field • 4-8 years’ professional experience applying machine learning in production or research-heavy environments; trading or financial markets exposure is highly desirable • Proven track record designing, training, and deploying predictive ML models in complex, data-rich environments • Deep understanding of ML theory and applied techniques, including neural networks, ensemble models, and probabilistic approaches • Proficiency in Python and experience with libraries such as PyTorch, TensorFlow, or JAX • Solid experience with large-scale data pipelines and distributed model training • Ability to bridge research and production - balancing innovation with practical execution and measurable results • Proven experience mentoring or managing research teams and driving collaborative, high-impact projects ...