Senior HPC and AI Networking Performance Research and Analysis Engineer
Nvidia · Shanghai, China
About this role
Nvidia is hiring a senior-level AI Research Scientist in the machine learning function based in Shanghai, China. The posting calls out experience with Python, C, Bash, CUDA and roughly 8+ years of relevant work. Listed education preference: a bachelor's degree or equivalent.
- Role
- AI Research Scientist
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Shanghai, China
- Experience
- 8+ years
- Education
- Bachelor's degree
- Posted
- Apr 20, 2026
More roles at Nvidia
Job description
from Nvidia careersNVIDIA is looking for a talented Performance Research and Analysis Engineer to join our Performance group. The ideal candidate will profile and analyze AI workloads on large GPUs and CPUs scale clusters for distributed Deep Learning LLM training and inference focusing at the communication patterns, collectives communication, RDMA, networking and system performance. You will work and interact with many types of HW platforms such as HCAs, Switches, CPUs, GPUs, Systems and also with various SW layers and features. You will experience with simulators and developing performance analysis tools and methodologies to dive deeply into the details, understand performance expectation, limitations, and bottlenecks as part of the root cause analysis of these jobs.
What you'll be doing:
Experience and research AI workloads and DL models specifically tailored for large-scale deep learning LLM training on NVIDIA supercomputers with a focus on High-performance networking.
Benchmarking, Profiling, and Analyzing the performance to find bottlenecks and identify areas of improvement and optimizations, with a strong emphasis on networking aspects.
Implement performance analysis tools.
Collaborating with many teams from HW to SW to provide performance analysis insights.
Define performance test planning, set performance expectations for new technologies and solutions, and work to reach the performance targets limits.
This is an excerpt. Read the full job description on Nvidia careers →