GPU Systems Engineer – High‑Performance Computing for Algorithmic Fund

About the role

Join a leading algorithmic trading firm as a GPU Systems Engineer, working within the Research and Development team to design, build and optimise large‑scale GPU compute clusters that power sophisticated HPC/AI research.

Key responsibilities

• Design, build and optimise distributed GPU compute clusters at petabyte scale.
• Identify and resolve performance bottlenecks across compute, storage and networking layers.
• Collaborate with R&D teams to profile, benchmark and fine‑tune GPU‑based workloads.
• Automate deployment, monitoring and troubleshooting for thousands of nodes.
• Lead critical infrastructure projects from concept through implementation and support.
• Test and deploy new hardware and software, partnering with vendors to resolve complex issues.

Required profile

• 5+ years of experience in large‑scale Linux systems engineering for HPC, AI or distributed infrastructure.
• Strong background in Linux installation, performance tuning and troubleshooting.
• Expertise in diagnosing distributed GPU workloads and GPU optimisation.
• Proficiency in Python scripting and automation frameworks.
• Experience with NVIDIA technologies such as CUDA, NCCL, GPUDirect RDMA and NVLink.
• Familiarity with configuration‑management tools (e.g., Salt, Ansible, Puppet, Chef).
• Excellent communication skills and ability to work across diverse technical teams.

Required skills

• Linux
• HPC
• Python
• CUDA
• C/C++
• NCCL
• GPUDirect RDMA
• NVLink
• Salt
• Ansible
• Puppet
• Chef