Software Engineer - AI/HPC Specialist

We are looking for software engineers to help scale and improve the efficiency of large AI training and inference for HW accelerators. A core part of this is optimising collective operations to enable optimised network utilisation for data sharing.This is an opportunity to work within a highly skilled team, collaborating with a large set of cross-functional partners and help bringing next generation large cluster architectures to life.

Software Engineer - AI/HPC Specialist Responsibilities:

• Work on collective communications stacks to optimise networking operations, leading to improved AI inference and training model performance
• Drive implementation of latency and bandwidth critical networking operations, as well as out-of-band signalling
• Debug custom and third party multi-host, accelerator enabled AI platforms
• Software development using C++/C and Python
• Work closely with other teams to deliver impact
• develop & improve features and innovations
• Extend and optimize large scale learning collective operations

• 3+ years of experience developing in C++/C and Python
• Experience with High Performance Computing/Networking or AI systems applications frameworks
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Specialized experience in one or more of the following machine learning/deep learning domains: Hardware accelerators, AI Infrastructure, or high performance networking
• Solid experience in debugging of distributed systems, revision control systems, testing, and CI pipelines

• Experience and understanding of AI/HPC systems
• Deep understanding of the transport stack (e.g. RDMA/RoCE, Infiniband, TCP/IP), its constraints and performance measures and how transport considerations enable the collective communications stack
• Experience in one or more of the following machine learning/deep learning domains: hardware accelerators, AI Infrastructure, and/or high performance computing (HPC), particularly pertaining to interconnect and collective communications stacks
• Familiarity with relevant tools, libraries, and frameworks (like PyTorch, NCCL, MPI, CUDA)