Expand infrastructure team to ensure researchers can work efficiently and effectively in a fast-paced environment due to growing data and computational demands for trading strategies.
Requirements
- Strong experience in HPC development, including parallel programming.
- Proficient in Python, C/C++, or similar languages used in scientific and quantitative computing.
- Familiar with ML frameworks and large-scale data pipelines.
- Worked with GPUs and/or custom accelerators like FPGAs.
- Experience in performance tuning and building tools that empower others to do their best work—especially in a trading or financial context.
Responsibilities
- Design and develop scalable, high-performance tools for data processing and ML workflows that support trading research and model development.
- Identify and resolve computational bottlenecks in large-scale systems used for quantitative analysis.
- Collaborate closely with quantitative researchers to understand their needs and translate them into robust, user-friendly tools.
- Build and maintain a research environment that is both powerful and easy to use, enabling rapid experimentation and deployment.
Other
