Senior Deep Learning Software Engineer, DLSim
At a glance
Senior Machine Learning Engineering role at NVIDIA. US, CA, Santa Clara · full-time.
In listing Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build simulation backends that let teams assess AI workloads quickly across NVIDIA compiler stacks
- Use modeled performance findings to improve deep learning kernel generation and computational graph optimization
- Model and optimize large-scale AI workloads and their deployment scenarios
- Work with architecture and software teams to assess future GPU features and inform chip and system design
What you bring
- A master's degree or equivalent experience in computer science, computer engineering or a related STEM field
- At least three years in compiler optimization, architectural simulation or a related area
- Hands-on experience with MLIR and compiler infrastructure
- Strong C/C++ and Python skills for software design, debugging, performance analysis and testing
Who this fits
This role suits a senior engineer focused on compiler infrastructure, hardware simulation and deep learning workloads. You’ll collaborate across architecture and software teams; a PhD is preferred.
From the employer
The DL Performance Modeling Team’s core mission is to deliver full stack simulation infrastructure for deep learning applications across a spectrum of GPUs. We actively collaborate with architecture, software, product, and research teams to shape and refine the strategic roadmap of DL hardware and software
We are now looking for a Deep Learning Software Engineer to help develop simulation infrastructure. The software rapidly assesses new AI-accelerating GPU hardware and software advancements.
What you’ll be doing:
Develop simulation backends that enable fast, scalable evaluation of AI workloads across NVIDIA compiler stacks.
Improve deep learning compiler kernel code generation and computational graph optimization using analysis based on modeled scenarios and performance insight.
Advance the modeling and optimization of datacenter-scale AI workloads and deployment scenarios.
Partner with architects and software teams to evaluate future GPU features and guide silicon and system-level design decisions.
What we need to see:
A Masters (or equivalent experience) in Computer Science, Computer Engineering, or a related STEM field; PhD preferred.
3+ years of relevant experience in compiler optimization, architectural simulation, or related areas.
Strong hands-on experience with MLIR and compiler infrastructure.
Excellent C/C++ and Python programming skills, including software design, debugging, performance analysis, and test development.
Strong communication and collaboration skills, with the ability to thrive in a fast-paced, multi-functional, outcome-focused environment.
Ways to stand out from the crowd:
Experience designing and building compiler frameworks or intermediate representations from the ground up.
Deep understanding of LLM inference workloads and their implications for computer architecture.
Hands-on experience implementing and optimizing complex AI workloads on CPUs, GPUs, or custom accelerators.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, collaborative and love a challenge, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 28, 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.