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Location
In office (Shanghai)
Seniority
Senior · 8+ years exp
Employment
Full-Time
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NVIDIA is an American technology company founded in 1993 that invented the graphics processing unit and has become the dominant supplier of accelerated computing platforms for artificial intelligence. Its portfolio spans data centre GPUs and systems built on the Hopper and Blackwell architectures, GeForce consumer graphics, automotive and robotics platforms, high-speed networking acquired with Mellanox, and the CUDA software stack that binds the ecosystem together. Headquartered in Santa Clara, California, the company sells to cloud providers, enterprises, research institutions and gamers worldwide and is one of the most valuable listed businesses on the Nasdaq.

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 experience) in CS, EE or CSEE and 5+ years; or MS and 8+ years of relevant work experience.

  • Strong background in deep learning and neural networks, in particular training.

  • Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.

  • Proven experience analyzing and tuning application performance.

  • Experience with processor and system-level performance modelling.

  • Programming skills in C++, Python, and CUDA.

  • Fluency in English

NVIDIA is increasingly known as the AI Computing company and 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. Are you passionate about performance? Are you interested in working on industry-leading Deep Learning products? Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field.

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