Senior Software Engineer, Deep Learning - Mlir Trt

NVIDIA · Semiconductors · Santa Clara, CA

Senior Software Engineer focused on developing and productizing deep learning solutions for autonomous driving vehicles, specifically involving compiler technology to optimize deep learning inference on NVIDIA hardware. The role requires expertise in deep learning frameworks, compiler technologies, and GPU programming.

What you'd actually do

  1. Developing compiler technologies to accelerate deep learning inference on NVIDIA hardware platforms for Physical AI.
  2. Working across a wide range of abstractions from model fine-tuning and quantization to low-level kernel development and performance optimization.
  3. Develop workflows that let users leverage frameworks (e.g. PyTorch, JAX) and compiler technologies tools (e.g. MLIR, Triton) without forgoing performance
  4. Work with customers to help accelerate their workloads on NVIDIA platforms.
  5. Stay up to date with the latest research and innovations in deep learning, implement and experiment with new insights to improve NVIDIA's Physical AI DNNs.

Skills

Required

  • MS or PhD degree in computer science, computer vision, robotics, computer architecture or equivalent experience in technical field
  • 5+ years of work experience in software development
  • 2+ years of experience in developing deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc.) or compiler technologies (e.g. LLVM, MLIR, TVM, Triton, etc.)
  • Domain experience in technologies used for GPU programming (e.g. CUDA C++ and/or DSLs like OpenAI Triton) or with system-level optimization for deep learning training or inference
  • Strong C/C++ programming skills
  • Familiar with start-of-the-art deep learning techniques for inference and training

Nice to have

  • Experience with MLIR or LLVM or similar compiler technologies
  • Background with low precision inference, quantization, compression of DNNs
  • Experience with GPU programming
  • Experience with building DSLs or optimizing compilers (e.g. graph compiler or kernel generator) for GPUs or other accelerated computing platforms
  • Open source project ownership or contribution, healthy GitHub repositories, guiding and/or mentoring experience

What the JD emphasized

  • developing deep learning frameworks
  • compiler technologies
  • deep learning inference
  • performance optimization
  • GPU programming

Other signals

  • develop compiler technology to allow larger and better models to be optimized to leverage NVIDIA’s unique hardware architecture
  • develop compiler technology to allow larger and better models to be optimized to leverage NVIDIA’s unique hardware architecture
  • develop compiler technology to allow larger and better models to be optimized to leverage NVIDIA’s unique hardware architecture