Machine Learning Engineer (M/W/D)

We are looking for an engineer with experience in low-level systems programming and optimisation to join our growing ML team. Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Your part here is optimising the performance of our models – both training and inference. We care about efficient large-scale training, low-latency inference in real-time systems and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking and host- and GPU-level considerations. There’s no fixed set of skills, but here are some of the things we’re looking for: An understanding of modern ML techniques and toolsets The experience and systems knowledge required to debug a training run’s performance end to end Background in Infiniband, RoCE, GPUDirect, PXN, rail optimisation and NVLink, and how to use these networking technologies to link up GPU clusters An understanding of the collective algorithms supporting distributed GPU training in NCCL or MPI Are you currently a student? * Major/Field of study Year you expect to begin full time employment #