Senior AI Training Performance Engineer
NVIDIA· Architect
Shanghaifull-timePosted 4mo ago
About the role
Senior AI Training Performance Engineer responsible for performance analysis and optimization across the AI training stack, from GPU architecture to deep learning frameworks, to maximize training speed on state-of-the-art hardware and software platforms.
Responsibilities
- Understand, analyze, profile, and optimize AI and deep learning training workloads on state-of-the-art hardware and software platforms.
- Understand the big picture of training performance on GPUs, prioritizing and solving problems across many dozens of state-of-the-art neural networks.
- Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
- Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
- Build tools to automate workload analysis, workload optimization, and other critical workflows.
Qualifications
- PhD (or equivalent experience) in CS, EE or CSEE and 5+ years; or MS and 8+ years of relevant work experience.
- Strong background in deep learning and neural networks, in particular training.
- Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.
- Proven experience analyzing and tuning application performance.
- Experience with processor and system-level performance modelling.
- Programming skills in C++, Python, and CUDA.
- Fluency in English.
Skills
Required:Deep learning and neural networks (training)Computer architecturePerformance analysis and tuningProcessor and system-level performance modellingC++PythonCUDAEnglish fluency
Last updated Jun 26, 2026. Interested? Apply on the company site.
About NVIDIA
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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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