GPU Systems Engineer
A top-tier proprietary trading firm is seeking a GPU Systems Engineer to join their global infrastructure team. You will play a critical role in designing, optimizing, and maintaining the GPU compute environments that support advanced quantitative research and machine learning pipelines in a low-latency trading context.
Key Responsibilities :
- Design and maintain GPU-based systems for high-throughput, low-latency workloads across research and production environments.
- Collaborate with quants, researchers, and engineering teams to deliver high-performance GPU compute infrastructure for model training, simulation, and real-time inference.
- Optimize GPU system configuration at the hardware, OS, and driver level, including memory, I / O, and thermal performance.
- Automate deployment, monitoring, and maintenance of GPU clusters using modern IaC and DevOps tools.
- Evaluate new GPU hardware, interconnects (e.g., NVLink, Infiniband), and vendor driver stacks to inform infrastructure strategy.
Qualifications :
Extensive experience managing and tuning GPU compute systems in production environments (NVIDIA preferred).Strong Linux systems engineering background, with deep understanding of kernel, drivers, and hardware interfaces.Experience with CUDA, NCCL, and GPU profiling / debugging tools (e.g., nvidia-smi, Nsight).Familiarity with orchestration tools and schedulers such as Kubernetes, Slurm, Airflow, or similar.Scripting and automation skills in Python, Bash, or equivalent.Knowledge of networking and storage optimization in high-throughput, distributed compute environments is a plus.Strong academic background in Computer Science, Electrical Engineering, or a related technical field.Join a technology-first trading firm with a collaborative culture, flat hierarchy, and significant investment in research infrastructure. Enjoy top-of-market compensation and the opportunity to work on some of the most challenging and impactful systems in the industry.
Apply now for a confidential discussion.