NVIDIA-posted 6 days ago
$148,000 - $287,500/Yr
Full-time • Senior
Hybrid • Us, CA
5,001-10,000 employees

We are now looking for a Senior Deep Learning Software Engineer, PyTorch-TensorRT Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of Torch inference with TensorRT! NVIDIA is rapidly growing our research and development for Deep Learning Inference and is seeking excellent Software Engineers at all levels of expertise to join our team. Companies around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in areas like Generative AI, Recommenders and Vision that have put DL into every software solution. Join the team that builds the software to enable the performance optimization, deployment and serving of these DL solutions. We specialize in developing GPU-accelerated Deep learning software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models. Collaborate with the deep learning community to integrate TensorRT to PyTorch. Identify performance opportunities and optimize SoTA models across the spectrum of NVIDIA accelerators, from datacenter GPUs to edge SoCs. Implement graph compiler algorithms, frontend operators and code generators across the PyTorch, Torch-TensorRT, TensorRT software stack. Work and collaborate with a diverse set of teams involving workflow improvements, performance modeling, performance analysis, kernel development and inference software development.

  • Analyze performance issues and identify performance optimization opportunities inside Torch-TensorRT/TensorRT.
  • Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to Torch-TensorRT/TensorRT/PyTorch.
  • Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to develop innovative inference solutions.
  • Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.
  • Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Science, Computer Engineering, EECS, AI)
  • At least 4 years of relevant software development experience
  • Excellent Python/C++ programming, software design and software engineering skills
  • Experience with a DL framework like PyTorch, JAX, TensorFlow
  • Experience with performance analysis and performance optimization
  • Architectural knowledge of GPU
  • Prior experience with a AoT or JiT compiler in deep learning inference, e.g. TorchDynamo/TorchInductor
  • Prior experience with performance modeling, profiling, debug, and code optimization of a DL/HPC/high-performance application
  • GPU programming experience and proficiency in one of the GPU programming domain specific languages, e.g. CUDA/TileIR/CuTeDSL/cutlass/Triton
  • You will also be eligible for equity and benefits .
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