Machine Learning Engineer – Deep Learning for HFT

About the role

Research, train, and evaluate deep learning models using large-scale order-book and market data to predict short-horizon market behavior. Own data and training pipelines, improve GPU and distributed-training performance, and collaborate on optimizing and integrating models into a latency-constrained C++ trading system. Requires a Master’s or PhD in a relevant quantitative discipline, or equivalent exceptional research and engineering ability, with 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.