英伟达Developer Technology Engineer – LLM
任职要求
• MS or PhD from a leading University in an engineering or Computer Science related field • 3+ years working experience • Strong and practical knowledge of programming techniques, and AI algorithms. • Experience in large-scale language model (LLM) training or inference, including the development of LLM frameworks and performance optimization. • Experience with parallel programming, ideally CUDA C/C++. • Excellent communication and organization skills, with a logical approach to problem solving, good time management and task prioritization. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family at www.nvidiabenefits.com/NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
工作职责
• Study and develop cutting-edge techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures. • Working on key applications (e.g., LLM training and inference) to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications. • Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models, by investigating the impact on application performance and developer efficiency. • Travel for on-site visits with developers and to conferences.
• Working directly with key application developers (especially LLM) to understand the current and future problems they are solving, creating and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications. This includes training and inference optimization for large language models, directly contributing to frameworks such as Megatron and TRTLLM, SGLang, vLLM... • Collaborating closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the design of next-generation architectures, software platforms, and programming models, including by investigating impact on application performance and developer productivity. • Engaging in deep optimization of high-performance operators, involving but not limited to CUDA deep optimization, instruction and compiler optimization. These optimizations will directly support customers or be integrated into products like cuDNN, cuBLAS, and CUTLASS... • Some travel is required for conferences and for on-site visits with developers.
• Understand China researcher and developer communities, Analyzing the technical requirement, identify needle moving projects. • Bridge NVIDIA tools with communities' requirements, Promote NVIDIA tools, libraries, and SDK’s with China researcher and developer communities, ISV and Service Providers. • Deeply understand AI4S, AI teaching, Agentic AI, Physical AI workflows and LLM breakthroughs, evolving ecosystem and alliances, attending conferences, building a network of influencers, and tracking opportunities in progress. • Discover new workflows, identify blockers to ISV adoption, and report back to the product teams. • Drive early adoption of new products and support launch and go-to-market activities. • Collaborate with NVIDIA business development managers, solution architects, developer technology engineers, developer marketing, product teams to engage with customers and communities. • We make heavy use of conferencing tools, but some travel is required. You are empowered to find the best way to get your job done and make our partners successful.
Key Responsibilities: Contribution: • Strong hands-on capability of migration, integration and cloud project implementation in specific domain. push the consumption growth objective. • Identifying customer needs in specific domain, and driving adoption and expansion. Lead product implementation. optimization, troubleshooting. • Model accountability in technical solution optimization, and ownership of both successes and failures that impact the technical solutions. Challenge: • Handle customer's issues using multiple approaches to identify optimal technical solution in specific domain. • Utilize Oracle and third-party data to gain a strategic, forward-thinking perspective on technical solutions. • Stay informed about evolving technical and business trends that may impact current or future projects. Expertise: • Apply deep knowledge of Oracle Cloud technologies, industry verticals, and market trends to design tailored solutions. • Continuously deepen your product and industry expertise, educating others and leveraging this knowledge to deliver impactful solutions.