The role

We are seeking a highly skilled Systems Engineer (Cloudmeter) to join our team to support benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimization and next-generation hardware development.

In this position, your responsibility will be to:

• Work closely with hardware, development teams to profile and analyze GPU performance at the system and kernel level.
• Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g., CUDA, ROCm).
• Perform acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.
• Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimizations on performance and scalability.

We expect you to have:

• Proficient in Unix/Linux, plus Python and Bash for automation.
• Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries
• Proven ability to troubleshoot complex system issues including hardware, software, and networking problems.
• Familiarity with containerized environments (e.g., Docker, Kubernetes).

Ways to stand out from the crowd:

• Experience with modern deep learning frameworks (PyTorch, JAX, vLLM, Tensort-LLM)
• Experience with job schedulers and resource managers (Slurm, Volcano, etc.).