Senior Deep Learning Software Engineer, Inference and Model Optimization

NVIDIA; Santa Clara (CA); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a senior software engineer to advance inference optimization for generative AI models, including LLMs and diffusion models, within the TRT Model Optimizer ecosystem.

You will leverage the Torch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile) to analyze graphs and implement high‑performance kernel techniques for automated deployment and scalable model support.

Qualifications

• Master's, PhD, or equivalent in CS/AI or related field.
• 8+ years in Deep Learning.
• Strong Python, PyTorch, and ML tools.
• Excellent software design, debugging, and testing.
• Strong communication and collaboration.

Responsibilities

• Design and optimize inference for LLMs and diffusion models.
• Develop high-performance kernels and automated deployment features.
• Collaborate across teams to scale model support and deployment.

Skills

Deep Learning

Python

PyTorch

Software Design

Algorithms

Communication

Independent Work

Education

Advanced Degree

Tools

TorchDynamo

torch.export

TorchCompile

CUDA

Job description

NVIDIA is at the forefront of the generative AI revolution! The Algorithmic Model Optimization Team specifically focuses on optimizing generative AI models such as large language models (LLM) and diffusion models for maximal inference efficiency using techniques ranging from neural architecture search and pruning to sparsity, quantization, and automated deployment strategies. Our work includes conducting applied research to improve model efficiency as well as developing an innovative software platform (TRT Model Optimizer). Our software is used both internally across NVIDIA and externally by research and engineering teams alike developing best-in-class AI models.

What You’ll Be Doing

• Train, develop, and deploy state-of-the generative AI models like LLMs and diffusion models using NVIDIA's AI software stack.
• 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 high-performance optimization techniques for inference, such as automated model sharding techniques (e.g. tensor parallelism, sequence parallelism), efficient attention kernels with kv-caching, and more.
• Collaborate with teams across NVIDIA to use performant kernel implementations within our 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.
• Play a pivotal role in architecting and designing a modular and scalable software platform to provide an excellent user experience with broad model support and optimization techniques to increase adoption.

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 (e.g. HuggingFace).
• 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 13, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

JR2027397