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Deep Learning Engineer - Distributed Task-Based Backends

NVIDIA

2.7

(9)

Multiple Locations (Remote)

#JR1986398

Position summary

rt enterprise customers and partners to scale novel models using our platform

  • Collaborate with Deep Learning software and hardware teams across NVIDIA, to drive development of future Deep Learning libraries

  • Contribute to the development of runtime systems that underlay the foundation of all distributed GPU computing at NVIDIA

What We Need To See:

  • BS, MS or PhD degree in Computer Science, Electrical Engineering or related field (or equivalent experience)

  • 5+ years of relevant industry experience or equivalent academic experience after BS

  • Proficient with Python and C++ programming

  • Strong background with parallel and distributed programming, preferably on GPUs

  • Hands-on development skills using Machine Learning frameworks (e.g. PyTorch, TensorFlow, Jax, MXNet, scikit-learn etc.)

  • Understanding of Deep Learning training in distributed contexts (multi-GPU, multi-node)

Ways To Stand Out From The Crowd:

  • Experience with deep-learning compiler stacks such as XLA, MLIR, Torch Dynamo

  • Background in performance analysis, profiling and tuning of HPC/AI workloads

  • Experience with CUDA programming and GPU performance optimization

  • Background with tasking or asynchronous runtimes, especially data-centric initiatives such as Legion

  • Experience building, debugging, profiling and optimizing multi-node applications, on supercomputers or the cloud

The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse 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.