Job Summary

• Machine learning is a critical pillar of Jane Street's global business, leveraging a unique, rapid-feedback trading environment for ML experimentation.
• The role involves optimizing the performance of ML models for both training and inference, encompassing large-scale training, low-latency real-time inference, and high-throughput research inference.
• The position requires a whole-systems approach, considering storage systems, networking, and host- and GPU-level factors, with a focus on understanding performance at the lowest level.

Matching Summary

Skills & Requirements

Key Requirements

• Experience in low-level systems programming and optimisation
• Understanding of modern ML techniques and toolsets
• Systems knowledge to debug training run performance
• Low-level GPU knowledge
• Debugging and optimisation experience with specific tools
• Library knowledge of specific ML/GPU libraries
• Intuition about CUDA characteristics
• Background in specific networking technologies
• Understanding of collective algorithms for distributed training
• Fluency in English

Work Rights