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Deep Learning Performance Architect Jobs (NOW HIRING)

Nvidia

Senior GPU Architect, Deep Learning

Austin, TX · On-site

The NVIDIA GPU Architecture group is looking for world class architects and software developers to ... highest performance in the world for deep learning and parallel processing algorithms. We are ...

Nvidia

Senior GPU Architect, Deep Learning

Durham, NC · On-site

The NVIDIA GPU Architecture group is looking for world class architects and software developers to ... highest performance in the world for deep learning and parallel processing algorithms. We are ...

Nvidia

Senior GPU Architect, Deep Learning

Austin, TX · On-site

The NVIDIA GPU Architecture group is looking for world class architects and software developers to ... highest performance in the world for deep learning and parallel processing algorithms. We are ...

Nvidia

Senior CPU Performance Architect

Austin, TX

$165K/yr

... deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming ... Come join the CPU performance architecture team and help us push performance boundaries for all our ...

Nvidia

Senior CPU Performance Architect

Hillsboro, OR · On-site

$181K/yr

... deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming ... Come join the CPU performance architecture team and help us push performance boundaries for all our ...

Nvidia

Senior CPU Performance Architect

Hillsboro, OR · On-site

$181K/yr

... deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming ... Come join the CPU performance architecture team and help us push performance boundaries for all our ...

Nvidia

Senior CPU Performance Architect

Santa Clara, CA · On-site

$196K/yr

... deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming ... Come join the CPU performance architecture team and help us push performance boundaries for all our ...

Nvidia

Senior CPU Performance Architect

Santa Clara, CA · On-site

$196K/yr

... deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming ... Come join the CPU performance architecture team and help us push performance boundaries for all our ...

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All JobsDeep Learning Performance Architect Jobs

Deep Learning Performance Architect information

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$156.5K

$168K

How much do deep learning performance architect jobs pay per year?

As of Sep 2, 2026, the average yearly pay for deep learning performance architect in the United States is $167,842.00, according to ZipRecruiter salary data. Most workers in this role earn between $167,000.00 and $167,000.00 per year, depending on experience, location, and employer.

What is a deep learning performance architect?

A Deep Learning Performance Architect is a specialized professional who designs, analyzes, and optimizes the performance of deep learning systems and models. They work to improve the efficiency, speed, and scalability of machine learning algorithms on various hardware platforms such as GPUs, TPUs, and CPUs. Their role often involves collaborating with software engineers and data scientists to identify bottlenecks and implement solutions that enhance computational capabilities for AI workloads. By doing so, they ensure that deep learning applications run faster and more efficiently, making the best use of available resources.

What are the key skills and qualifications needed to thrive as a deep learning performance architect?

To thrive as a Deep Learning Performance Architect, you need a strong background in computer science, deep learning frameworks, parallel computing, and optimization techniques, typically supported by a relevant degree and experience in AI or high-performance computing. Familiarity with tools such as TensorFlow, PyTorch, CUDA, and profiling or benchmarking systems is essential. Analytical problem-solving, effective communication, and a collaborative mindset help professionals excel in cross-functional teams and resolve complex performance bottlenecks. These skills are vital for optimizing AI workloads, ensuring scalability, and maximizing the efficiency of deep learning models in production environments.

What are some common challenges faced by deep learning performance architects when optimizing large-scale neural network models?

Deep Learning Performance Architects often encounter challenges such as balancing model accuracy with computational efficiency, managing memory constraints on specialized hardware, and optimizing inference or training speed across different platforms. They frequently need to profile and analyze bottlenecks at both the algorithmic and hardware levels, often requiring close collaboration with software engineers and hardware designers. Staying current with rapidly evolving deep learning frameworks and hardware accelerators is also essential to ensure optimal performance and scalability.

What is the difference between Deep Learning Performance Architect vs Machine Learning Engineer?

AspectDeep Learning Performance ArchitectMachine Learning Engineer
CredentialsAdvanced degrees in AI, deep learning, or related fields; certifications in deep learning frameworksDegrees in computer science, data science, or related fields; certifications in machine learning tools
Work EnvironmentResearch labs, AI development teams, performance optimization settingsData-driven projects, model development, deployment environments
Industry UsageTech companies, AI research firms, organizations focusing on deep learning optimizationTech companies, startups, enterprises applying machine learning solutions

The Deep Learning Performance Architect specializes in optimizing deep learning models for efficiency and scalability, focusing on hardware and software performance. In contrast, Machine Learning Engineers develop, train, and deploy machine learning models across various applications. While both roles require strong technical skills, the Architect emphasizes performance tuning and system optimization, whereas the Engineer focuses on model development and implementation.

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Deep Learning Performance Architect jobs near you
Infographic showing various Deep Learning Performance Architect job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $167,842 per year, or $80.7 per hour.

Senior GPU Architect, Deep Learning

Nvidia

Durham, NC

Full-time

Re-posted yesterday

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

We are now looking for a Senior GPU & Deep Learning Architect!

The NVIDIA GPU Architecture group is looking for world class architects and software developers to join and lead our various architecture efforts. A key part of NVIDIA's strength is to innovate in the graphics and parallel computing fields delivering the highest performance in the world for deep learning and parallel processing algorithms. We are constantly looking for ways to improve our GPU architecture, especially for deep learning workloads, both training and inference, and maintain our leadership by developing new parallel programming models, and new architectures required to make this successful. In this position, you will be responsible for developing and enhancing various features in the GPU architecture that advance the state of the art in parallel programming models or parallel computing performance. You would interact with other world-class architects and researchers to build simulators, mapping deep learning workloads to current and future hardware, and validate new architectural features.

What you'll be doing:

  • Design new hardware features for future processing architectures targeted at deep learning workloads, for both training and inference.

  • Advance the state of parallel computation.

  • Be knowledgeable about future parallel programming models and their impact to hardware.

  • Develop software for various hardware simulators, test infrastructures or metrics systems including databases.

  • Work in a team to document, design, develop tools to analyze and simulate, validate, and verify functional or performance models.

  • Develop tests, testplans, and testing infrastructure for new graphics or parallel processing architectures

  • Be hungry to learn and work on simulators, RTL and real silicon.

What we need to see:

  • MS in Computer Science, Electrical Engineering or Computer Engineering or equivalent experience.

  • Experience in working with hardware targeted at deep learning, or working on mapping deep learning algorithms to hardware.

  • 8+ years of relevant industry experience in GPU or other parallel programming architectures (or other equivalent experience).

  • Strong programming ability inC, C++, Perl andPython.

  • Background in computer architecture, parallel processing, signal processing and/or high performance computing.

  • Knowledge of state of the art in DL algorithms and attention mechanisms is a huge plus.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our GPU Architecture team and help us build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly 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

Get the full story on Breakroom

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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

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