Senior Performance Software Engineer, Deep Learning Libraries

NVIDIA

. Write highly tuned compute kernels for core deep learning operations, including matrix multiplies, convolutions, and normalizations .

Posted 9/20/2026full-timeShanghai • ChinaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing optimized compute kernels for deep learning operations, with strong proficiency in C++ programming and performance-oriented parallel programming. Demonstrated ability to collaborate with cross-functional teams to enhance deep learning performance on NVIDIA GPUs.

Highest-signal resume keywords

C++ ProgrammingDeep Learning OptimizationPerformance-Oriented Parallel ProgrammingComputer ArchitectureNVIDIA GPU Development

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Applicant Tracking System Keywords

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Hard Skills

Compute KernelsMatrix MultiplicationConvolutionsNormalizationsRegression TestingCI/CD FlowsPerformance AnalysisDebuggingAssembly ProgrammingResource Optimization

Tools & Technologies

NVIDIA cuDNNNVIDIA cuBLASTensorRTOpenMPPthreads

Industry Keywords

Deep LearningLinear AlgebraPerformance OptimizationThroughput ImprovementSoftware Engineering Best Practices

Tech Stack

Tools & technologies

AssemblyC++

About the role

Key responsibilities & impact

Write highly tuned compute kernels for core deep learning operations, including matrix multiplies, convolutions, and normalizations
Follow software engineering best practices, including regression testing and CI/CD flows
Collaborate with the CUDA compiler team to generate optimal assembly code
Collaborate with deep learning training and inference performance teams to identify layers requiring optimization
Collaborate with hardware and architecture teams on the programming model for new deep learning hardware features
Develop optimized code to accelerate linear algebra and deep learning operations on NVIDIA GPUs
Deliver high-performance code to NVIDIA cuDNN, cuBLAS, and TensorRT libraries

Requirements

What you’ll need

Masters or PhD degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or related field
2+ years of relevant industry experience
Demonstrated strong C++ programming and software design skills, including debugging, performance analysis, and test design
Experience with performance-oriented parallel programming, even if it’s not on GPUs (e.g. with OpenMP or pthreads)
Solid understanding of computer architecture and some experience with assembly programming
Ability to identify bottlenecks, optimize resource utilization, and improve throughput