Deep Learning Software Engineer, TensorRT Performance - New College Grad 2027

Company: Nvidia

Location: US, CA, Santa Clara (Remote)

Salary: $124k - $195.5k per year

Type: Full-time

Remote: Yes

Posted: 2026-10-12

About this role

We are now looking for a Deep Learning Software Engineer, TensorRT Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of NVIDIA’s inference ecosystem! 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 inference solutions. We specialize in developing GPU-accelerated deep learning inference software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models.

Collaborate with the deep learning community to integrate TensorRT into OSS frameworks like TensorRT-EdgeLLM and 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 NVIDIA’s inference ecosystem. Work and collaborate with a diverse set of teams involving workflow improvements, performance modeling, performance analysis, kernel development and inference software development.

What you'll be doing:

  • Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA’s inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT)
  • Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT.
  • Develop new model pipelines for NVIDIA’s inference ecosystem with optimized performance including but not limited to areas like quantiza...

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