英伟达Deep Learning Performance Architect
任职要求
• BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,)
• 3+ years of working experience in relevant directions (e.g., hardware system, datacenter hardware, LLM workloads on data center) will be a plus
• Be familiar with GPU or a…工作职责
NVIDIA is developing GPU and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, performance projections, analysis and optimization effort. In this position, you will have the chance to analyze deep learning performance on different hardware and software architecture and make a significant impact in a dynamic technology focused company What you’ll be doing :• Analyze performance of various deep learning workloads on different architectures • Identify architecture and software performance bottlenecks • Explore new features and system configurations to achieve better performance and energy efficiency
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
• Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products • Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency. • Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations. • Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product 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
• Design and develop the architecture, interface and features of the GPU kernel library • Keep improving the quality and performance of the library and its GPU kernels • Explore and expand the boundary of innovative technologies like GPU code generation and fusion • Contribute to NVIDIA's AI business by collaborating closely with DL product teams as well as kernel development teams