Machine Learning Engineer – Deep Learning for HFT

About the role

Research, train, and evaluate deep learning models on large-scale order-book and market data, owning data preparation, training pipelines, and rigorous out-of-sample experiments. Optimize model training and inference, integrate models into a latency-constrained C++ trading system, and use production feedback to guide further research. Requires a Master’s or PhD in a quantitative or related discipline, or equivalent exceptional research and engineering ability, and typically 3–10 years of relevant experience. Candidates should have hands-on experience training deep learning models at scale, strong Python and PyTorch or JAX skills, proficiency in C++, Rust, or CUDA, and a rigorous experimental track record.