About the job
Jane Street is seeking a talented engineer with a strong background in low-level systems programming and optimization to join our dynamic Machine Learning team.
As a key component of Jane Street's global operations, machine learning plays a pivotal role in our continually evolving trading environment. This unique setting offers rapid feedback for ML experimentation, enabling us to seamlessly integrate fresh ideas into our processes.
Your primary responsibility will be to enhance the performance of our machine learning models during both training and inference phases. We prioritize efficient large-scale training, low-latency inference in real-time systems, and high-throughput inference for research purposes. This involves improving standard CUDA implementations, while also adopting a holistic approach that considers storage systems, networking, and both host and GPU-level factors. Furthermore, we aim to ensure our platform's efficiency down to the granular level—how effective is our throughput? How long does it realistically take to load a vector from the L2 cache?
If finance is not your primary background, rest assured—you are not alone. Many of our team members come from diverse fields. If you possess a curious mindset and a passion for tackling challenging problems, you will likely find a home here.