Nvidia Senior Deep Learning Software Engineer 

United States, California 

535374030

What you’ll be doing:

• Play a pivotal role in defining of a modular, scalable platform to seamlessly bridge training and deployment workflows—enabling tight integration of deployment tooling with training frameworks such as Megatron and Nemo

• Leverage and build upon the torch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile, etc...) to analyze and extract standardized model graph representation from arbitrary torch models for our automated deployment solution.

• Develop support for inference optimization techniques such as speculative decoding and LoRA.

• Collaborate with teams across NVIDIA to use performant kernel implementations within the automated deployment solution.

• Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities.

• Continuously innovate on the inference performance to ensure NVIDIA's inference software solutions (TRT, TRT-LLM, TRT Model Optimizer) can maintain and increase its leadership in the market.

What we need to see:

• Masters, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related field.

• 8+ years of relevant work or research experience in Deep Learning.

• Excellent software design skills, including debugging, performance analysis, and test design.

• Strong proficiency in Python, PyTorch, and related ML tools.

• Strong algorithms and programming fundamentals.

• Good written and verbal communication skills and the ability to work independently and collaboratively in a fast-paced environment.

Ways to stand out from the crowd:

• Contributions to PyTorch, JAX, or other Machine Learning Frameworks.

• Knowledge of GPU architecture and compilation stack, and capability of understanding and debugging end-to-end performance.

• Familiarity with NVIDIA's deep learning SDKs such as TensorRT.

• Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.