英伟达Senior AI Training Performance Engineer
任职要求
We are now looking for a Senior AI Training Performance Engineer!
NVIDIA is seeking senior engineers who are obsessed with performance analysis and optimization to help us squeeze every last clock cycle out of AI training, one of the most important workloads in the world. If you are unafraid to work across all layers of the hardware/software stack from GPU architecture to Deep Learning Framework to achieve peak performance, we want to hear from you! This role offers the opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution while helping deep learning users around the globe enjoy ever-higher training speeds.
What you will be doing:
• Understand, analyze, profile, and optimize AI and deep learning training workloads on state-of-the-art hardware and software platforms.
• Understand the big picture of training performance on GPUs, prioritizing and then solving problems across many dozens of state-of-the-art neural networks.
• Implement production-quality software in multiple layers of NVIDIA's deep learning platform stack, from drivers to DL frameworks.
• Implement key DL training workloads in NVIDIA's proprietary processor and system simulators to enable future architecture studies.
• Build tools to automate workload analysis, workload optimization, and other critical workflows.
What we want to see:
• PhD (or equivalent experien…工作职责
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• Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings • Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers • Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more • Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure • Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them • Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.
Joining NVIDIA's DGX Cloud Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on optimizing efficiency and resiliency of AI workloads, as well as developing scalable AI and Data infrastructure tools and services. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. We are seeking an AI infrastructure software engineer to join our team. You'll be instrumental in designing, building, and maintaining AI infrastructure that enable large-scale AI training and inferencing. The responsibilities include implementing software and systems engineering practices to ensure high efficiency and availability of AI systems.As a senior DGX Cloud AI Infrastructure software engineer at NVIDIA, you will have the opportunity to work on innovative technologies that power the future of AI and data science, and be part of a dynamic and supportive team that values learning and growth. The role provides the autonomy to work on meaningful projects with the support and mentorship needed to succeed, and contributes to a culture of blameless postmortems, iterative improvement, and risk-taking. If you are seeking an exciting and rewarding career that makes a difference, we invite you to apply now! What you’ll be doing: • Develop infrastructure software and tools for large-scale AI, LLM, and GenAI infrastructure. • Develop and optimize tools to improve infrastructure efficiency and resiliency. • Root cause and analyze and triage failures from the application level to the hardware level • Enhance infrastructure and products underpinning NVIDIA's AI platforms. • Co-design and implement APIs for integration with NVIDIA's resiliency stacks. • Define meaningful and actionable reliability metrics to track and improve system and service reliability. • Skilled in problem-solving, root cause analysis, and optimization.
NVIDIA is now looking for LLM Train Framework Engineers for the Megatron Core team. Megatron Core is open-source, scalable, and cloud-native frameworks built for researchers and developers working on Large Language Models (LLM) and Multimodal (MM) foundation model pretraining and post-training. Our GenAI Frameworks provide end-to-end model training, including pretraining, alignment, customization, evaluation, deployment, and tooling to optimize performance and user experience. Build on Megatron Core Framework's capabilities by inventing advanced distributed training algorithms and model optimizations. Collaborate with partners to implement optimized solutions. What you’ll be doing: • Build and develop open source Megatron Core. • Address extensive AI training and inference obstacles, covering the entire model lifecycle including orchestration, data pre-processing, conducting model training and tuning, and deploying models. • Work at the intersection of AI applications, libraries, frameworks, and the entire software stack. • Spearhead advancements in model architectures, distributed training strategies, and model parallel approaches. • Enhance the pace of foundation model training and optimization through mixed precision formulas and advanced NVIDIA GPU structures. • Performance tuning and optimizations of deep learning framework and software components. • Research, prototype, and develop robust and scalable AI tools and pipelines.
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