Senior Deep Learning Algorithm Engineer
我们现在正在寻找一名高级 DL 算法工程师！NVIDIA 正在寻求熟悉性能分析和优化的高级工程师，以帮助我们将每一个最后一次钟周期从深度学习培训中挤出出来。这是当今世界上最重要的工作负载之一。如果你不害怕在硬件/软件堆的所有层面上工作，从 GPU 架构到深度学习框架，实现最高绩效，我们希望听到你！这个角色提供了一个机会直接影响快速发展的 AI 技术公司中的硬件和软件路线图，同时帮助全球深度用户享受更高的培训速度。· 了解，分析，配置和优化深度学习培训和推断工作负载在最先进的硬件和软件平台上。· 与 NVIDIA 各地的研究人员和工程师合作，提供工作负载性能提高方面的指导。· 在 NVIDIA 的深度学习平台堆中实现生产质量软件。· 建立工具来自动化工作负荷分析，工作负荷优化和其他关键的工作流程。我们希望看到的是：· 5年以上经验。· CS, EE 或 CSEE 或相等体验中的 MSc 或博士学位。· 深度学习和神经网络的强有背景，无论是培训和结论。· 深入了解计算机架构，并熟悉 GPU 架构的基础知识。·经验证明分析，建模和调整应用程序性能。·C++和 Python 编程技能。脱而出群众的方式：·与现代 LLM 推理框架 （TRT-LLM,vLLM,Ollama 等）经验。·强大的算法基本知识。·深度学习模型生产部署经验。•对处理器和系统级绩效建模经验证实。·GPU 编程经验 （CUDA 或 OpenCL）是一个强大优势，但不需要。随着 NVIDIA 进入数据中心业务，我们的团队发挥了最大的作用，使我们不断增长的数据中心部署充分利用并建立基于数据的硬件设计和系统软件开发方法。我们与 NVIDIA 的广泛跨界团队合作，从 DL 研究小组到 CUDA Kernel 和 DL 框架开发小组，到架构团队。随着我们的团队的成长以及我们寻求识别和利用长期机会，我们的技能将会变得更加丰富。
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We are now looking for a Senior DL Algorithms Engineer! NVIDIA is seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning training, one of today's most essential 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 an 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 deep learning training and inference workloads on state-of-the-art hardware and software platforms.
- Collaborate with researchers and engineers across NVIDIA, providing guidance on improving the performance of workloads.
- Implement production-quality software across NVIDIA's deep learning platform stack.
- Build tools to automate workload analysis, workload optimization, and other critical workflows.
What we want to see:
- 5+ years of experience.
- MSc or PhD in CS, EE or CSEE or equivalent experience.
- Strong background in deep learning and neural networks, both training & inference.
- Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.
- Proven experience analyzing, modeling and tuning application performance.
- Programming skills in C++ and Python.
Ways to stand out from the crowd:
- Experience with modern LLM inference frameworks (TRT-LLM, vLLM, Ollama, etc.)
- Strong fundamentals in algorithms.
- Experience with production deployment of Deep Learning models.
- Proven experience with processor and system-level performance modelling.
- GPU programming experience (CUDA or OpenCL) is a strong plus but not required.
As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing data center deployments and establishing a data-driven approach to hardware design and system software development. We collaborate with a broad cross-section of teams at NVIDIA ranging from DL research teams to CUDA Kernel and DL Framework development teams, to Silicon Architecture Teams. As our team grows and as we seek to identify and take advantage of long-term opportunities, our skills needs are growing as well. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
Originally posted on Himalayas