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Deep Learning Performance Architect Jobs (NOW HIRING)

Nvidia

Senior CPU Performance Architect

Austin, TX · On-site

$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

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 ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

Deep Learning Engineer As a Deep Learning Engineer at Carbon Robotics, you will contribute to ... Communicate model architecture decisions, tradeoffs, and performance results to both technical and ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for ... model architecture decisions, tradeoffs, and performance results to both technical and non ...

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 ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for ... model architecture decisions, tradeoffs, and performance results to both technical and non ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for ... model architecture decisions, tradeoffs, and performance results to both technical and non ...

Nvidia

Senior CPU Performance Architect

Austin, TX · On-site

$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

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 ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

$140K - $220K/yr

Communicate model architecture decisions, tradeoffs, and performance results to both technical and ... Deep understanding of foundational deep learning mathematics and the ability to apply first ...

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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 Aug 13, 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 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 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 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.

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.
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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 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $167,842 per year, or $80.7 per hour.

Senior CPU Performance Architect

Nvidia

Austin, TX • On-site

$165K/yr

Full-time

Re-posted 5 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 244 rated software companies

Job description

Do you want to help drive the development of CPU technology for architectures used for artificial intelligence (AI) / deep learning (DL), high-performance computing (HPC), cloud service providers (CSP), gaming, virtual reality, and autonomous vehicles? Come join the CPU performance architecture team and help us push performance boundaries for all our CPU products!

What you'll be doing:

  • Work on workload bring-up and performance analysis/projection, both on silicon and full-system simulator.

  • Study workloads for a wide range of markets, including AI/DL, CSP, HPC, and autonomous vehicles.

  • Study real world use-cases and identify critical application behavior and reduce to directed test cases.

  • Analyze and debug performance scaling bottlenecks on multi-core and multi-socket CPU and CPU/GPU systems.

  • Work with CPU and interconnect architects to improve future CPU and system designs based on your findings.

  • Benchmark NVIDIA's CPU offerings against competition and suggest software or hardware improvements.

What we need to see:

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

  • 12+ years of relevant experience.

  • Experience with CPU workloads and performance analysis.

  • Knowledge of performance test development and benchmarking for CPU and I/O.

  • Deep knowledge of CPU microarchitecture and system architecture.

  • Experience with the ARM instruction set architecture (ISA) preferable but not required.

Ways to stand out from the crowd:

  • PhD or Research experience.

  • GPU driver experience.

  • Knowledge of GPU-accelerated workloads andmodeling performance of accelerated workloads.

  • Experience with performance optimization of AI frameworks such as PyTorch.

NVIDIA is a global leader in accelerated computing, delivering breakthroughs in AI, HPC, and advanced system design. Our technologies power transformative applications across industries - from robotics and autonomous vehicles to healthcare and climate research.With the introduction of theGrace CPU Superchip, and more recently, the announcement of the Vera CPU, NVIDIA has expanded into the CPU server market, complementing our world-class GPUs and SoCs. These CPUs play a critical role in orchestrating complex workloads with exceptional performance-per-watt efficiency. The CPU architecture team is driving innovations that integrate seamlessly with NVIDIA's broader technology stack, enabling faster AI model training, agentic use-cases, efficient data processing, and scalable cloud deployments.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 12, 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

Year founded

1993

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