Senior Deep Learning Software Engineer, Inference and Model Optimization
Company websitenvidia.com (NVIDIA, opens in new tab)
Base salary $184,000 to $356,500
Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSanta Clara, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (24 min ago) · observed since
About this job
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.
We are now looking for a Senior Deep Learning Software Engineer to develop and scale up our automated inference and deployment solution. As part of the team, you will be instrumental in pushing the limits of inference efficiency and large-scale, automated deployment. Your work will touch upon fundamental aspects of a typical machine learning stack including working in high-level frameworks like PyTorch and HuggingFace to developing and improving high-performance kernel implementations in CUDA, TRT-LLM, and Triton. This is an exceptional opportunity for passionate software engineers straddling the boundaries of research and engineering, with a strong background in both machine learning fundamentals and software architecture & engineering.
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.
Increasingly known as “the AI computing company” and widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Are you creative, motivated, and love a challenge? If so, we want to hear from you! Come, join our model optimization group, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly-growing field.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: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 November 3, 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.Source: NVIDIA on Workday · View original posting (opens in new tab)
Pay in context
This role's base floor ($184,000) is above 46% of the 1,507 Data & ML roles in California listed on this site; 30 others list the same floor. Their median floor is $188,000; the middle half runs from $159,311 to $229,700.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingSenior Deep Learning Software Engineer, Inference and Model Optimization$184,000 to $356,500
Senior Software Engineer, Subnet Management$184,000 to $356,500
Senior Software Engineer, AI Networking$184,000 to $356,500
Senior Software Engineer, Machine Learning Safety$184,000 to $356,500
Senior Firmware Security Architect, Networking$184,000 to $356,500
Senior Compiler Engineer - AI$184,000 to $287,500
Senior System Software Engineer, Performance - CUDA Driver$184,000 to $356,500
Chart as a table
| Role | Published base |
|---|---|
| Senior Deep Learning Software Engineer, Inference and Model Optimization (this listing) | $184,000 - $356,500 |
| Senior Software Engineer, Subnet Management | $184,000 - $356,500 |
| Senior Software Engineer, AI Networking | $184,000 - $356,500 |
| Senior Software Engineer, Machine Learning Safety | $184,000 - $356,500 |
| Senior Firmware Security Architect, Networking | $184,000 - $356,500 |
| Senior Compiler Engineer - AI | $184,000 - $287,500 |
| Senior System Software Engineer, Performance - CUDA Driver | $184,000 - $356,500 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-10-30
Where this pay comes from
Location as the employer wrote it: US, CA, Santa Clara • US, Remote (Levels 4-5 combined)
184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
