Senior Deep Learning Systems Architect

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Senior Deep Learning Systems Architect to design hardware accelerator and processor architectures for next-generation GPUs and systems that advance AI. The role involves understanding AI/DL workloads, mapping them to hardware, identifying optimizations, and prototyping solutions. Requires a strong background in ML/DNNs, training frameworks, numerical analysis, performance optimization, and computer architecture, with significant experience in C++ and Python.

What you'd actually do

  1. As a member of our deep learning architecture team, you will contribute to features that help next-generation GPUs and systems advancing the state of AI.
  2. This position requires you to keep up with the latest DL research and collaborate with diverse teams (internal and external to NVIDIA), including DL researchers, hardware architects, and software engineers.
  3. As a system architect for NVIDIA’s offerings for AI systems, you will participate in engineering projects and co-design architecture for systems from conception, specification and prototyping.
  4. Understanding various AI/DL workloads and their mapping to underlying HW and Systems. Identifying potential improvements and bottlenecks, proposing solutions to address existing gaps, and accelerate/improve current systems/methods.
  5. Comprehensive analyses from first principles of various deep learning techniques, system optimizations to build out analytical models as well as implementing prototypes, and benchmarking to test/prove ideas.

Skills

Required

  • MS (or equivalent experience) or PhD degree in computer science, computer architecture, electrical engineering or related field
  • Machine learning (with focus on Deep Neural Networks)
  • solid understanding of DL fundamentals
  • Experience adapting and training DNNs for various tasks
  • Experience developing code for one or more of the DNN training frameworks (such as PyTorch, TensorFlow or JAX)
  • Numerical analysis
  • Performance analysis and optimization
  • Computer architecture
  • Programming fluency with C++
  • Programming fluency with Python

Nice to have

  • GPU computing (CUDA, OpenCL, OpenACC)
  • HPC (MPI, OpenMP)

What the JD emphasized

  • 10+ years of relevant work experience
  • Strong background in at least a few of the following relevant areas is required in your work history

Other signals

  • design hardware accelerator and processor architectures
  • deep learning architecture team
  • next-generation GPUs and systems advancing the state of AI
  • co-design architecture for systems from conception, specification and prototyping
  • Understanding various AI/DL workloads and their mapping to underlying HW and Systems
  • Comprehensive analyses from first principles of various deep learning techniques, system optimizations
  • implementing prototypes, and benchmarking to test/prove ideas