高级深度学习框架通信工程师
Senior Deep Learning Framework Communications Engineer
NVIDIA 在人工智能、高性能计算和可视化领域引领着突破性的发展。我们发明的 GPU 是现代计算机的视觉皮层，是我们的产品和服务的核心。我们的工作开启了新的宇宙供探索，激发了令人惊叹的创造力和发现，并推动了从人工智能到自动驾驶汽车等曾经的科幻发明。
我们正在寻找一位有动力的深度学习工程师，将先进的通信技术引入 AI 堆栈，包括 PyTorch、TRT-LLM、vLLM、SGLang、JAX 等。你将与开发通信库如 NCCL、NVSHMEM 以及 GPUDirect 技术的团队一起工作，用于扩展深度学习和 HPC 应用。你的客户对多 GPU 的需求多种多样，从可扩展至 100K GPU 的训练到微秒级延迟的推理。GPU 之间的通信性能直接影响 AI 应用。你在 AI 工具包中的工作将使这些变得更简单。对于有 AI 背景的人而言，这是一个提升该领域技术水平的绝佳机会。你准备好为创新技术的发展做出贡献，并帮助实现 NVIDIA 的愿景了吗？
你将负责：
- 在 AI 框架中集成新的通信库功能：从概念验证到性能分析再到生产
- 对 AI 工作负载和框架进行深入分析，以识别多 GPU 通信需求和机会。与最新 AI 模型开发团队紧密合作。
- 改进 AI 编译器，以隐藏通信或执行自动融合。
- 在多 GPU 集群上进行深入的 AI 工作负载性能分析。
- 为大规模或动态 AI 工作负载设计容错和弹性解决方案。
- 编写自定义通信或融合计算-通信内核，以在 NV 平台上展示最佳性能。
- 影响通信库（NCCL 和 NVSHMEM）的发展路线图。
- 与跨多个时区的动态团队合作。
我们希望看到：
- 计算机科学或相关领域的学士、硕士或博士学位（或同等经验），并具有 5 年以上的软件工程和 HPC/AI 经验
- 具有深度学习框架（如 PyTorch、JAX）或推理引擎（如 TRT-LLM、vLLM、SGLang）的开发或集成经验
- 使用 Python、C++、CUDA 或相关技术进行快速原型设计和开发的能力
查看英文原文
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.
We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What you will be doing:
- Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
- Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.
- Improve AI compilers to hide communications or perform automatic fusion.
- Conduct in-depth AI workload performance characterization on multi-GPU clusters.
- Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
- Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.
- Influence the roadmap of communication libraries - NCCL & NVSHMEM.
- Collaborate with a very dynamic team across multiple time zones.
What we need to see:
- B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience
- Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang
- Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe)
- Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)
- Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)
- Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)
- Adaptability and passion to learn new areas and tools
- Flexibility to work and communicate effectively across different teams and timezones
Ways to stand out from the crowd:
- Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
- Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes
- Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 11, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Originally posted on Himalayas