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Deep Learning Kernel Software Performance Architect

NVIDIA· Architect
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Hybrid (Shanghai), Hybrid (Beijing)Full-timePosted 3mo ago

About the role

Software Performance Architect focused on optimizing GPU kernel performance for state-of-the-art data-center platforms, building automated, data-driven workflows to detect, explain, and prevent performance regressions in deep learning workloads.

Responsibilities

  • Performance analysis, optimization and debugging
  • Build performance narratives using structured methodology: baselines, projections, controlled comparisons, and regression attribution.
  • Analyze performance of GPU-accelerated kernels and key deep learning building blocks, identify gaps with baselines or projections, then optimize the kernels' performance to fill the gaps.
  • Debug performance issues end-to-end: reproduce, isolate root causes, propose fixes or mitigation paths, and drive closure with the owning teams.
  • Automation + regression infrastructure (Python-heavy)
  • Develop and maintain Python-based automation for performance testing and analysis—using modern AI-assisted developer tools to accelerate scripting while keeping code maintainable and reviewable.
  • Design and operate performance test workflows: coverage definition, test/workload generation, automated large-scale execution (CI/nightly/on-demand), rerun rules, and reproducibility standards.
  • Cross-team collaboration and operating model
  • Work with kernel developers and the compiler teams to ensure performance checks are practical, scalable, and aligned to release needs.
  • Work with chip architecture and modeling teams to solidify the performance methodology across chip architecture generations and common Deep Learning operators such as GEMM, Attention, MoE.
  • Partner with SWQA and infrastructure teams for execution at scale and reliable pipelines/dashboards.
  • Following general software engineering best practices including support for regression testing and CI/CD flows.

Qualifications

  • Masters or PhD degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or related field
  • Strong programming ability in Python plus C/C++ with 2+ working experience (performance-oriented code reading/debugging)
  • Solid fundamentals in computer architecture, parallel programming and performance reasoning (latency/throughput, memory hierarchy, parallelism) to be able to identify bottlenecks, optimize resource utilization, and improve throughput
  • Experience with performance analysis workflows: profiling, measurement methodology, reproducibility, and regression triage.
  • Comfortable working across teams and driving issues to decision/closure with clear communication

Skills

Required:PythonC/C++Performance analysisComputer architecture

Benefits

  • Not specified in provided description
Last updated Jul 10, 2026. Interested? Apply on the company site.

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