AI Insights
NVIDIA

Deep Learning Performance Architect

NVIDIA · Santa Clara, California, US
full-timesenior (4-10 yrs)Posted 21d ago
Software EngineeringIC3ICOn-siteVisa Sponsored
StackC++CPythonCUDAOpenCLGPU ProgrammingTensorRTDeep LearningPerformance ProfilingPerformance OptimizationKernel DevelopmentCPU ArchitectureGPU ArchitecturePerformance ModelingSoftware DesignAgile

Summary

NVIDIA is hiring Software Engineers and Senior Software Engineers to develop GPU-accelerated deep learning inference software, including highly optimized kernels and performance tuning for TensorRT, working cross-functionally with automotive, image, and speech understanding teams.

About the role

We are expanding our research and development for Inference. We seek excellent Software Engineers and Senior Software Engineers to join our team.

We specialize in developing GPU-accelerated Deep learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in numerous areas. Join the team that builds software to enable new solutions. Collaborate with the deep learning community to implement the latest algorithms for public release in Tensor-RT. Your ability to work in a fast-paced customer-oriented team is required and excellent communication skills are necessary. 

What you’ll be doing:

  • Develop highly optimized deep learning kernels for inference

  • Do performance optimization, analysis, and tuning

  • Work with cross-collaborative teams across automotive, image understanding, and speech understanding to develop innovative solutions

  • Occasionally travel to conferences and customers for technical consultation and training

What we need to see: 

  • Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)

  • SW Agile skills helpful

  • Excellent C/C++ programming and software design skills

  • Python experience a plus

  • Performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU

  • GPU programming experience (CUDA or OpenCL) desired

  • 4 years of relevant work experience

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!

What you'll do

1Develop highly optimized deep learning kernels for inference
2Perform performance optimization, analysis, and tuning on GPU hardware
3Collaborate with cross-functional teams in automotive, image understanding, and speech understanding to develop innovative solutions
4Implement the latest deep learning algorithms for public release in TensorRT
5Occasionally travel to conferences and customer sites for technical consultation and training

Requirements

4+ years of experience with strong C/C++ programming and software design for high-performance systems
Hands-on GPU programming experience using CUDA or OpenCL for compute-intensive workloads
Demonstrated proficiency in performance modeling, profiling, debugging, and code optimization at the CPU/GPU architecture level
Advanced degree (MS or PhD) in Computer Engineering, Computer Science, or AI/related discipline, or equivalent practical experience
Ability to collaborate cross-functionally across automotive, vision, and speech domains in a fast-paced, customer-oriented environment

Nice to have

Python
OpenCL
Agile methodologies
TensorRT

Role overview

Role family
Software Engineering
Level
IC3 — ml_ai
Experience
4–10 years
Type
Individual Contributor
Remote policy
On-site
Visa sponsorship
Available

Tech stack analysis

LANGUAGES
CC++Python
FRAMEWORKS
TensorRT
INFRASTRUCTURE
CUDAOpenCLGPU
TOOLS
Performance profiling toolsDebuggers

Salary estimate

$175K – $260K
AI-estimated salary range
Confidence78%
Reasoning

NVIDIA is a top-tier semiconductor/AI company in Santa Clara, CA. Senior SWE roles at NVIDIA with GPU/ML specialization typically command $175K–$260K base salary, with significant additional stock compensation (RSUs) and bonuses. The 4+ years experience requirement and MS/PhD preference push this toward the senior band. Comparable NVIDIA roles on Levels.fyi show total compensation well above $300K when including equity.

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Green flags

4 items
NVIDIA is at the epicenter of the AI/GPU revolution — exceptional career growth and industry relevance for deep learning engineers.growth

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Benefits breakdown

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Hiring insights

JD quality
5/10
Urgency
medium
Autonomy
high
Team size
medium (5-15)

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Red flags

PRO4 items
No salary or compensation range disclosed — atypical for California-based roles and potentially non-compliant with CA pay transparency norms.transparency

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Interview insights

PRO
Rounds
5
Duration
4 wks
Difficulty
very hard
Take-home
Yes

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Career path

PRO
Next roles
Staff ML Systems EngineerPrincipal Deep Learning EngineerML Infrastructure Architect

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About the company

NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.

HQSanta Clara, CA, USA
Interview difficultyvery hard
Build vs Maintainbuild
Cross-functionalYes