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Nvidia Deep Learning Engineer Datacenters 
India, Karnataka, Bengaluru 
936439064

01.12.2024

What you'll be doing:

  • Help develop software infrastructure to characterize and analyze a broad range Deep Learning applications
  • Evolve cost-efficient datacenter architectures tailored to meet the needs of Large Language Models (LLMs).
  • Work with experts to help develop analysis and profiling tools in Python, bash and C++ to measure key performance metrics of DL workloads running on Nvidia systems.
  • Analyze system and software characteristics of DL applications.
  • Develop analysis tools and methodologies to measure key performance metrics and to estimate potential for efficiency improvement.

What we need to see:

  • A Bachelor’s degree in Electrical Engineering or Computer Science with 3 years or more of relevant experience (Masters or PhD degree preferred)
  • Experience in at least one of the following:
    • System Software: Operating Systems (Linux), Compilers, GPU kernels (CUDA), DL Frameworks (PyTorch, TensorFlow).
    • Silicon Architecture and Performance Modeling/Analysis: CPU, GPU, Memory or Network Architecture
  • Experience programming in C/C++ and Python. Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm) is a plus
  • Demonstrated ability to work in virtual environments, and a strong drive to own tasks from beginning to end. Prior experience with such environments will make you stand out.

Ways to stand out from the crowd:

  • Background with system software, Operating system intrinsics, GPU kernels (CUDA), or DL Frameworks (PyTorch, TensorFlow).

  • Experience with silicon performance monitoring or profiling tools (e.g. perf, gprof, nvidia-smi, dcgm).

  • In depth performance modeling experience in any one of CPU, GPU, Memory or Network Architecture

  • Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm).

  • Prior experience with multi-site teams or multi-functional teams.