英伟达Computer Architecture Intern - 2025
任职要求
• MS Degree in relevant discipline (CS, EE, Math). PhD helpful • Expert programming skills in C or C++ • Strong background in computer architecture, parallel processing, signal processing and/or high performance computing • Experience in characteri…
工作职责
• Enhance GPU architecture to extend the state of the art in performance, efficiency, programmability and reliability • Analyze, tune and prototype key applications for new GPU architectures • Build model to predict performance, power and reliability on future architecture • Design and develop tools to analyze, simulate, validate, and verify application performance and energy consumption • Collaborate across the company to guide the direction of GPU computing, working with software, research and product team
• Develop and refine software solutions to expedite LLM SW stack (could be within inference/post train or pre-train phase) by harnessing the power of GPU technology. • Collaborate closely with a world-class team of engineers to implement and refine GPU-based algorithms. • Analyze and determine the most effective methods to improve performance, ensuring seamless execution across diverse computing environments. • Engage in both individual and team projects, contributing to NVIDIA's mission of leading the AI revolution. • Work in an empowering and inclusive environment to successfully implement groundbreaking AI solutions.
• Enhance GPU architecture to extend the state of the art in performance, efficiency, programmability and reliability • Analyze, tune and prototype key applications for new GPU architectures • Build model to predict performance, power and reliability on future architecture • Design and develop tools to analyze, simulate, validate, and verify application performance and energy consumption • Collaborate across the company to guide the direction of GPU computing, working with software, research and product team
• You will develop and optimize software solutions to accelerate LLM inference using GPU technology. • Collaborate closely with a world-class team of engineers to implement and refine GPU-based algorithms. • Analyze and determine the most effective methods to improve performance, ensuring seamless execution across diverse computing environments. • Engage in both individual and team projects, contributing to NVIDIA's mission of leading the AI revolution. • Work in an empowering and inclusive environment to successfully implement groundbreaking AI solutions.
Design and develop generative video models for high-fidelity, controllable synthesis. Build infrastructure for large-scale training, evaluation, and benchmarking of video models. Investigate model consolidation and shared representation learning across video understanding and generation tasks. Optimize algorithms for runtime, power, memory, and temporal quality on-device. Collaborate with product and research teams to integrate video generation technologies into Apple’s camera and video pipelines.