A leading HFT fund is seeking research scientists to apply machine learning to generate cutting-edge capabilities in complex domains, particularly in generating signals from unstructured data.
Requirements
- Minimum 5+ years' demonstrable experience creating ML systems with real metrics & impact in industry and/or academia
- Strong general ML background with some exposure to language modeling architectures, e.g. transformers, SSMs
- Solid development skills in Python and/or C++
- Familiarity with ML libraries/frameworks, e.g. PyTorch (preferred), TensorFlow, and/or JAX
- Ability to reason through quantitative problems
- Experience with HPC and distributed large model training
- Experience with GPU performance optimization or end-to-end model development, particularly in LLMs
Responsibilities
- Lead an open-ended research project from concept to production.
- Find compelling problems well-suited to current and projected LLM capabilities.
- Collaborate extensively with trading teams to understand requirements & constraints.
- Continuously improve model design, tools, and infrastructure.
- Work on projects that may include any area of the quant research process with potential for business-wide application.
- Apply emerging techniques and models to generate signals from unstructured data.
- Combine emerging techniques and models with original research.
Other
- Demonstrated ability to communicate effectively with trading researchers
- Minimum 5+ years' experience
- Not applicable to fresh graduates
- Ability to work in a high volume application environment
