英伟达Deep Learning Kernel Software Performance Architect
任职要求
• 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, measuremen…
工作职责
• Performance analysis, optimization and debugging• Build performance narratives using structured methodology: baselines, projections, controlled comparisons, and regression attribution. • With the methodologies, 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 (e.g., Cursor/Claude Code/Copilot) 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
We are now looking for a Deep Learning Performance Software Engineer!We are expanding our research and development for deep learning. We seek excellent Software Engineers and Senior Software Engineers to join our team. We specialize in developing GPU-accelerated Deep learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in numerous areas. Join the team that builds software to enable new solutions. Your ability to work in a fast-paced customer-oriented team is required and excellent communication skills are necessary. What you’ll be doing: • Develop compilers and DSLs for deep learning workloads • Design and implement highly optimized deep learning kernels • Continuously improve the compiler architecture for current and next generation chips • Perform performance analysis on emerging AI workloads and integrate with AI frameworks
• Build, maintain, and improve CI infrastructure that supports development, verification, and release of NVIDIA’s deep learning compiler stacks across GPU and accelerator environments • Improve CI reliability and signal quality by reducing flakes, improving reproducibility, strengthening diagnostics, and making correctness and performance failures easier to understand and act on • Apply automation, AI, and agent-based workflows to reduce manual CI operations, speed up failure triage, and improve developer efficiency • Build reusable and self-service CI platforms that support multiple products, projects, model suites, hardware targets, and software configurations while partnering closely with compiler, infrastructure, and release teams
We are now looking for a Deep Learning Performance Software Engineer!We are expanding our research and development for Inference. We seek excellent Software Engineers and Senior Software Engineers to join our team. We specialize in developing GPU-accelerated Deep learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in numerous areas. Join the team that builds software to enable new solutions. Collaborate with the deep learning community to implement the latest algorithms for public release in Tensor-RT. Your ability to work in a fast-paced customer-oriented team is required and excellent communication skills are necessary. What you’ll be doing: • Develop highly optimized deep learning kernels for inference • Do performance optimization, analysis, and tuning • Work with cross-collaborative teams across automotive, image understanding, and speech understanding to develop innovative solutions • Occasionally travel to conferences and customers for technical consultation and training