GPU Systems Engineer

Overview

In this role you will design, build, and optimize large-scale distributed GPU compute clusters to support HPC/AI research at HRT. You will work with cross-functional teams across compute, storage, OS, and automation to keep global research and trading operations running 24/7. You’ll profile, benchmark, and tune GPU workloads, identify bottlenecks, and automate deployment and monitoring across thousands of nodes. The role offers high impact through infrastructure projects that scale with cutting-edge technology and global data centers, shaping the performance of our AI-driven research ecosystem.

Pay / Benefits

• base salary 150,000–300,000 USD/year
• discretionary bonuses
• medical/dental/vision
• basic life insurance
• retirement savings plans
• sick and parental leave/Different PTO including 20 vacation days and 10 holidays

Responsibilities

• Design, build, and optimize large-scale distributed GPU compute clusters
• Identify and resolve GPU workload bottlenecks across compute, storage, and networking layers
• Collaborate with research/engineering teams to profile, benchmark, and fine-tune GPU workloads
• Automate system deployment, monitoring, and troubleshooting across thousands of nodes
• Collaborate with teams to support evolving workloads
• Own critical infrastructure projects from concept to implementation and support
• Test and deploy new hardware and software; partner with vendors to resolve complex issues

Key requirements

• 5+ years of experience in large-scale Linux systems engineering in HPC, AI or distributed infrastructure roles
• Extensive experience in Linux system installation, performance tuning, and troubleshooting
• Expertise in troubleshooting distributed GPU workloads
• Deep knowledge around GPU optimization and performance
• Proficiency in Python scripting and automation frameworks
• CUDA or C/C++ experience is a plus
• Experience with NVIDIA technologies beyond CUDA (NCCL, GPUDirect RDMA, NVLink)
• Familiarity with configuration management tools (Salt, Ansible, Puppet, Chef)
• Comfort diagnosing complex system issues at hardware, OS, and network levels
• Strong communication and organizational skills; collaboration across diverse teams
• Thrive in fast-paced, high-impact environments

• 强良好的沟通能力
• 组织能力
• 跨团队协作
• Linux HPC/AI系统架构
• GPU性能优化与调优
• GPU工作负载排错

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