Jane Street seeks a highly skilled engineer to optimize machine learning model performance across training and inference systems, focusing on low-level systems programming, GPU optimization, and innovative problem-solving in a dynamic trading environment.
Primary responsibilities include optimizing machine learning models' performance in both training and inference contexts, with a focus on efficient large-scale training, low-latency real-time systems, and high-throughput research inference.
Required experience includes deep technical expertise in GPU computing, systems programming, performance debugging, distributed training technologies, and advanced networking infrastructure, demonstrating comprehensive understanding of modern machine learning toolsets and optimization techniques.
The role offers an opportunity to work in a cutting-edge quantitative trading firm that values collaborative problem-solving, technological innovation, and provides a unique platform for rapid ML experimentation with minimal implementation friction.
