1 day ago
Shanghai, ChinaIntern
Responsibilities
- Benchmark, profile, and analyze AI and HPC workloads on NVIDIA supercomputers and distributed systems.
- Aggregate benchmark data and produce written reports for sales, marketing, software, and hardware teams.
- Build benchmark automation using AI agents and agentic coding tools while ensuring reliable and reproducible results.
- Collaborate with internal teams to debug and resolve performance issues.
- Configure hardware and software systems to run benchmarks.
Requirements
- Currently pursuing a bachelor’s degree or higher in Computer Science, Electrical Engineering, or a related field.
- Experience programming and debugging with Python or Unix shell and hands-on experience with Linux-based systems.
- Familiarity with container platforms such as Docker.
- Fluency with AI coding assistants and agentic workflows, including the ability to verify generated output.
- Hands-on experience with TensorRT-LLM, vLLM, or SGLang, or experience deploying and training AI model inference systems.
- Strong data analysis, written reporting, and English verbal and written communication skills.
- Preferred experience includes CI/CD pipelines, DevOps practices, cloud provisioning, Kubernetes, Slurm, agent workflows, MCP tools, reusable agent skills, GPUs, TPUs, cloud systems, performance benchmarking, and system-level problem solving.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.