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Salaried Deep Learning Jobs (NOW HIRING)

We are now seeking a Senior Deep Learning Performance Architect! NVIDIA is looking for outstanding ... Your base salary will be determined based on your location, experience, and the pay of employees in ...

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered ... Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

Senior Deep Learning Compiler Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered ... Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

Senior Deep Learning Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered ... Deep Learning and Autonomous Vehicles. Your base salary will be determined based on your location ...

We are now seeking a Senior Deep Learning Performance Architect! NVIDIA is looking for outstanding ... Your base salary will be determined based on your location, experience, and the pay of employees in ...

We are now looking for a Senior GPU & Deep Learning Architect! The NVIDIA GPU Architecture group is ... Your base salary will be determined based on your location, experience, and the pay of employees in ...

Showing results 21-40

Salaried Deep Learning information

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$11K

$83.9K

$140K

How much do salaried deep learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for salaried deep learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is the difference between Salaried Deep Learning vs Salaried Machine Learning Engineer?

AspectSalaried Deep LearningSalaried Machine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; experience with neural networksMaster's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural network modelsTech companies, data-driven firms, AI product development teams
Employer & Industry UsagePrimarily in AI research, academia, and companies developing deep learning modelsAcross industries like finance, healthcare, and e-commerce implementing ML solutions

While both roles involve machine learning, Salaried Deep Learning specialists focus on neural network architectures and AI research, whereas Salaried Machine Learning Engineers work on broader ML applications and deployment across various industries.

More about Salaried Deep Learning jobs

What cities are hiring for Salaried Deep Learning jobs?

Cities with the most Salaried Deep Learning job openings:

What are the most commonly searched types of Deep Learning jobs?

The most popular types of Deep Learning jobs are:

What states have the most Salaried Deep Learning jobs?

States with the most job openings for Salaried Deep Learning jobs include:

Infographic showing various Salaried Deep Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

Senior Deep Learning Performance Architect

Nvidia Corporation

Santa Clara, CA • On-site

$196K/yr

Full-time

Re-posted 20 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies


Job description

We are now seeking a Senior Deep Learning Performance Architect!
NVIDIA is looking for outstanding Performance Architects with a background in performance analysis, performance modeling, and AI/deep learning to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.
What you'll be doing:
  • Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
  • Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites
  • Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
  • Develop, analyze, and harness groundbreaking Deep Learning frameworks, libraries, and compilers
  • Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

What we need to see:
  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience
  • 6+ years of meaningful work experience
  • Strong background in GPU or Deep Learning ASIC architecture for training and/or inference
  • Experience with performance modeling, architecture simulation, profiling, and analysis
  • Solid foundation in machine learning and deep learning
  • Strong programming skills in Python, C, C++

Ways to stand out from the crowd:
  • Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT)
  • Experience with relevant libraries, compilers, and languages - CUDNN, CUBLAS, CUTLASS, MLIR, Triton, CUDA, OpenCL
  • Experience with the architecture of or workload analysis on other DL accelerators
  • Demonstration of self-motivation, with a knack for critical thinking and thinking outside the box

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as "the AI computing company", NVIDIA wants you! Come, join our Deep Learning Architecture team, where you can help build real-time, efficient computing platforms driving our success in this exciting and rapidly growing field.
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 January 13, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993