GPU Systems Engineer – High‑Performance Computing for Algorithmic Fund

About the role

Join a world‑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 cutting‑edge HPC/AI research.

Key responsibilities

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

Required profile

• 5+ years of experience in large‑scale Linux systems engineering for HPC, AI or distributed infrastructures.
• Strong background in Linux installation, performance tuning and system‑level troubleshooting.
• Proven ability to diagnose complex hardware, OS and network issues.
• Excellent communication and collaboration skills across diverse technical teams.

Required skills

• Linux system administration
• Python scripting and automation frameworks
• GPU optimisation and performance analysis
• CUDA (or C/C++)
• NVIDIA technologies such as NCCL, GPUDirect RDMA, NVLink
• Configuration management tools (e.g., Salt, Ansible, Puppet, Chef)

What we offer

• Opportunity to work on cutting‑edge HPC/AI infrastructure in a fast‑paced, high‑impact environment.
• Collaboration with top researchers from mathematics, physics, computer science and engineering.
• Access to world‑class computing resources and a culture of scientific innovation.