About the Company
A quantitative research firm applies scientific methods to complex problems in finance. It builds machine learning and high-performance computing platforms that turn research into tradable signals.
Responsibilities
•Evaluate and integrate cutting-edge ML accelerators and HPC technologies
•Optimize model inference for extreme latency and throughput requirements
•Benchmark distributed training setups and assess networking and storage trade-offs
•Engage with leading technology vendors and influence their product roadmaps
•Design and implement solutions, from rapid proofs of concept to robust system architectures
Requirements
•Hold a postgraduate degree in Machine Learning or a related quantitative field, or have equivalent commercial experience building ML systems at scale
•Have strong object-oriented programming skills, particularly with Python, PyTorch, and NumPy
•Have deep expertise in at least one of the following: advanced optimization methods, modern ML techniques, high-performance computing, profiling, or model inference
•Have demonstrated ability to evaluate and integrate novel ML/HPC technologies and engage with external experts and vendors
Conditions
Not specified in the posting.
