Principal Developer, AI Networking

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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 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 NVIDIA N, 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. The AI Networking Codesign and Benchmarking R D group requires a senior software engineer. In this exciting role, you will profile, analyze, and optimize AI workloads on large-scale GPU and CPU clusters used for distributed Deep Learning LLM training and inference. Your primary focus will be collectives communication and networking. You will work across hardware components such as HCAs, Switches, CPUs, GPUs, and Systems. You will also engage with software layers including LLM applications, machine learning frameworks, communication, and computing libraries. Moreover, you will build performance analysis tools and strategies to investigate details and clarify performance expectations, limitations, and bottlenecks. This is your chance to contribute to AI innovation! What you'll be doing: Characterizing AI workloads and deep learning models aimed at large-scale LLM training and inference on NVIDIA supercomputers. The role centers on distributed systems with a focus on high-performance networking and NVIDIA communication libraries. Benchmarking, profiling, and analyzing the performance to find bottlenecks and identify areas for improvement and optimizations, with a strong emphasis on networking aspects. Developing PyTorch trace-based profiling, analysis, and replaying toolset to aid in benchmarking, debugging, and co-designing network systems for LLM workloads. Collaborating with multiple teams from hardware to software to provide performance analysis insights. Defining performance test plans, setting performance expectations for new technologies and solutions, and working to achieve performance targets. What we need to see: B.Sc in Computer Science or Software Engineering or equivalent experience. 15+ years of experience with high-performance networking (RDMA, MPI, NCCL, SHARP). Demonstrated ability in performance evaluation techniques and approaches. Experience with NVIDIA GPUs and the CUDA library. Knowledge of deep learning frameworks like TensorFlow or PyTorch. Expertise in networking collective communication libraries such as NCCL and protocols like RoCE and RDMA. Fast and self-learning capabilities with strong analytical and problem-solving skills. Proficiency in programming languages: Python, Bash, and C++. Experience with a container-based development environment. Great teammate who communicates clearly and works well with others. Ways to stand out from the crowd: Extensive understanding and hands-on experience with AI workloads and benchmarking for distributed LLM training. Knowledge in PyTorch, CUDA, and NCCL libraries. Comprehensive system knowledge and understanding (Intel / AMD / ARM CPUs, NVIDIA GPUs, HCA, Memory, PCI). Strong capabilities in performance evaluation and methods using contemporary tools. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar

NVIDIA 致力于变革计算机图形学、PC 游戏和加速计算领域已超过 25 年。这是一份独特的创新传承，由卓越的技术和杰出的人才共同驱动。如今，我们正在挖掘 AI 的无限潜力，以定义下一个计算时代。在这个时代，我们的 GPU 将成为计算机、机器人和自动驾驶汽车的大脑，使它们能够理解世界。做前所未有的事情需要远见、创新和世界上最优秀的人才。作为 NVIDIA 的一员，您将沉浸在一个多元、支持性的环境中，每个人都被激励着发挥最佳水平。加入团队，看看您如何对世界产生持久的影响。AI 网络协同设计与基准测试研发团队需要一名高级软件工程师。在这个令人兴奋的职位中，您将对用于分布式深度学习 LLM 训练和推理的大规模 GPU 和 CPU 集群上的 AI 工作负载进行分析、剖析和优化。您的主要关注点将是集合通信和网络。您将跨硬件组件工作，如 HCA、交换机、CPU、GPU 和系统。您还将与软件层互动，包括 LLM 应用、机器学习框架、通信和计算库。此外，您将构建性能分析工具和策略，以调查细节并阐明性能预期、限制和瓶颈。这是您为 AI 创新做出贡献的机会！

您将要做的事情：

- 表征面向 NVIDIA 超级计算机上大规模 LLM 训练和推理的 AI 工作负载和深度学习模型。该职位以分布式系统为核心，重点关注高性能网络和 NVIDIA 通信库。
- 进行基准测试、剖析和分析性能，以发现瓶颈并确定改进和优化的领域，重点关注网络方面。
- 开发基于 PyTorch trace 的剖析、分析和重放工具集，以协助 LLM 工作负载的基准测试、调试和网络系统协同设计。
- 与从硬件到软件的多个团队合作，提供性能分析洞察。
- 定义性能测试计划，为新技术的解决方案设定性能预期，并努力实现性能目标。

我们需要看到的：

- 计算机科学或软件工程学士学位或同等经验。
- 15 年以上高性能网络（RDMA、MPI、NCCL、SHARP）经验。
- 在性能评估技术和方式方面有证明的能力。
- 具有 NVIDIA GPU 和 CUDA 库的经验。
- 了解 TensorFlow 或 PyTorch 等深度学习框架。
- 精通 NCCL 等网络集合通信库以及 RoCE 和 RDMA 等协议。
- 快速自主学习能力，具有强大的分析和解决问题的能力。
- 精通编程语言：Python、Bash 和 C++。
- 具有基于容器的开发环境经验。
- 优秀的团队成员，沟通清晰，与他人合作良好。

脱颖而出的方式：

- 对分布式 LLM 训练的 AI 工作负载和基准测试有广泛的理解和实践经验。
- 具备 PyTorch、CUDA 和 NCCL 库的知识。
- 全面的系统知识和理解（Intel / AMD / ARM CPU、NVIDIA GPU、HCA、内存、PCI）。
- 在使用现代工具进行性能评估和方法方面具有强大的能力。

凭借具有竞争力的薪酬和丰厚的福利待遇，我们被广泛认为是技术世界中最令人向往的雇主之一。我们拥有世界上最具前瞻性和最勤奋的人才为我们工作，并且由于前所未有的增长，我们独家的工程团队正在迅速壮大。如果您是一位有创造力且自主的工程师，对技术充满真正的热情，我们期待您的消息。您的 base salary 将根据您的地点、经验以及类似

⚑ 岗位信息收录自公开招聘页（Himalayas），以雇主官网为准