Senior DL Engineer – Inference & Model Optimization (Equity)

NVIDIA; United States; Remote; USD 184,000 - 356,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Deep Learning Software Engineer to advance automated inference and deployment for generative AI models, including LLMs and diffusion models. You will push limits of inference efficiency, work with PyTorch and CUDA-based stacks, and help design a scalable platform for broad model support.

Ideal candidates have strong ML fundamentals, extensive DL software experience, and a track record of high‑performance kernel development.

Qualifications

• Masters, PhD, or equivalent in Computer Science, AI, Applied Math, or related field.
• 8+ years of relevant work or research experience in Deep Learning.
• Excellent software design, debugging, performance analysis and test design.

Responsibilities

• Train, develop, and deploy state‑of‑the generative AI models like LLMs and diffusion models.
• Leverage Torch 2.0 ecosystem to analyze and extract graph representations for automated deployment.
• Develop high‑performance optimization techniques for inference such as tensor parallelism and efficient attention kernels.

Skills

Python

PyTorch

HuggingFace

CUDA

Algorithms

Education

Master's degree or PhD in CS/AI/Applied Math

Tools

CUDA

Triton

TensorRT

Job description

NVIDIA is seeking a Senior Deep Learning Software Engineer to advance automated inference and deployment for generative AI models, including LLMs and diffusion models. You will push limits of inference efficiency, work with PyTorch and CUDA-based stacks, and help design a scalable platform for broad model support.

Ideal candidates have strong ML fundamentals, extensive DL software experience, and a track record of high‑performance kernel development.