英伟达Developer Technology Engineer, AI
任职要求
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 30 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What You'll Be Doing: • Working directly with key application developers 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 reference code 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. • Need to travel from time to time for conferences and for on-site visits with developers. What We Need To See: • A BS, MS, or PhD degree from a leading university in an engineering or computer science related field (or equivalent experience). While not a requirement, domain expertise in LLM, CTR, CV, or HPC, is helpful. • 3+ years experience, programming proficiency in C/C++ and/or Python with a deep understanding of software design, programming techniques, and algorithms. • 2+ years experience with LLM training framework development and performance optimization. • Strong mathematical fundamentals, including linear algebra and numerical methods. • Experience with parallel programming, ideally CUDA C/C++. • Strong communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills. 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 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.#deeplearning
工作职责
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• 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. • Work directly with key customers to understand the current and future problems they are solving and provide the best AI solutions using GPUs. • Collaborate 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.
• 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.
• 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.
We are looking for a Generative AI Intern Engineer to join the NVIDIA Developer Technology group (Devtech) and work with a team of experienced engineers on innovative uses of AI for games and content creation. The Devtech team works with NVIDIA researchers and leading game developers to bring cutting edge AI research from across NVIDIA and the industry to gamers and 3D professionals in high performance packages such as real-time inferenced graphics, physics and animations. What you’ll be doing: • Research and implement innovative generative AI algorithms for game engines and authoring tools, including real-time neural graphics, physics based animation and diffusion models. • Develop neural graphics, animation and physics models and maintain open-source projects for both game-making and user runtimes. Integrate them into mainstream game engines and DCC tools. • Use various optimization techniques, such as tensor fusion and quantization, to fit the AI models onto user devices and maximize the performance of inference for real-time gaming. • Collaborate with game developers on optimizations and improvements for specific GenAI applications. • Interact closely with the architecture and driver teams at NVIDIA in ensuring the best possible experience on current generation hardware, and on determining trends and features for next generation architectures.