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Deep Learning Performance Architect Jobs (NOW HIRING)

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

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

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

$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

$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 ...

Compunnel

Performance Architect

Milpitas, CA · On-site

$194K/yr

Job Summary T he Performance Architect develops advanced AI storage solutions through innovative ... Deep expertise in optimizing large-scale ML systems and GPU architectures. * Proven technical ...

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

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 ...

Sandisk

Performance Architect

Milpitas, CA

$190K/yr

Responsible for improving the AI/ML ASIC Architecture performance through hardware & software co ... Deep experience optimizing large-scale ML systems, GPU architectures * Strong track record of ...

Apple

Systems Performance Architect

Beaverton, OR

$147K - $272K/yr

... learning new things from deep technical topics to user workflows. Strong interpersonal skills and ability to work with multi-disciplinary teams. Good communication and presentation skills Minimum ...

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 ...

Sandisk

Performance Architect

Milpitas, CA · On-site

$136K - $226K/yr

Responsible for improving the AI/ML ASIC Architecture performance through hardware & software co ... Deep experience optimizing large-scale ML systems, GPU architectures * Strong track record of ...

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All JobsDeep Learning Performance Architect Jobs

Deep Learning Performance Architect information

See salary details

$156.5K

$168K

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

As of Jun 26, 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 the highest paid type of architect?

Among various architecture roles, enterprise architects and solutions architects tend to have the highest salaries, especially in technology and IT sectors. Deep Learning Performance Architects, as specialized roles in AI and machine learning, also command high compensation, particularly with advanced skills in neural networks, cloud platforms, and performance optimization. Overall, roles requiring specialized technical expertise and strategic responsibilities typically offer the highest pay in architecture fields.

What are the key skills and qualifications needed to thrive as a Deep Learning Performance Architect, and why are they important?

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.

Is ML a high paying job?

Deep Learning Performance Architects and related machine learning roles are generally well-paid due to the specialized skills required, such as expertise in neural networks, programming, and data analysis. Salaries tend to be higher than average, especially with experience, advanced degrees, and proficiency in tools like TensorFlow or PyTorch.

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.

How much does a deep learning architect make at Nvidia?

A deep learning architect at Nvidia typically earns between $150,000 and $200,000 annually, depending on experience, location, and level of expertise. Compensation may also include bonuses, stock options, and benefits, reflecting the company's competitive pay structure for specialized AI roles.

What does a deep learning architect do?

A deep learning performance architect designs and optimizes neural network models and infrastructure to improve AI system efficiency and accuracy. They work with frameworks like TensorFlow or PyTorch, analyze model performance, and implement solutions to enhance scalability and speed in machine learning applications.
More about Deep Learning Performance Architect jobs
What job categories do people searching Deep Learning Performance Architect jobs look for? The top searched job categories for Deep Learning Performance Architect jobs are:
Deep Learning Performance Architect jobs near you
Infographic showing various Deep Learning Performance Architect job openings in the United States as of June 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $167,842 per year, or $80.7 per hour.
Performance Architect

Performance Architect

Advanced Micro Devices, Inc

Austin, TX • On-site

$142K/yr

Full-time

Posted 14 days ago

Advanced Micro Devices rating

8.4

Company rating: 8.4 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

22nd of 139 rated electronics manufacturers

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture. We push the limits of innovation to solve the world's most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE:
As a Performance Architect in Embedded Processor Architecture, Engineering & Solutions (EPAES) team, you will provide deep technical expertise and technical leadership in analyzing and optimizing performance of workloads running on AMD x86 processors.
THE PERSON:
The successful person has the ability to establish and drive to goals including plan of record, timelines, budget, scope, performance and quality will be critical to success. A passion for creating plans and working with a diverse list of internal and external customers is necessary for this critical and highly visible role. This role involves customer engagement in architecture and performance initiatives. Professionalism, excellent verbal and written communication skills and occasional traveling are required.
The applicant must be a team player who makes and meets commitments, as well as demonstrate an aptitude to thrive in a fast paced, multi-tasking environment.
KEY RESPONSIBILITIES:
  • Develop in-depth knowledge of the architecture and micro-architecture of the various AMD x86 processor families as well as performance analysis tools
  • Set up and analyze target workloads, including applications and benchmarks, for networking, security/firewall, storage, wireless infrastructure, edge computing, industrial IoT, automotive, and embedded market segments.
  • Characterize workload performance and develop optimized recipes for maximizing application performance and showcasing strong differentiation of AMD based solutions.
  • Collaborate with customers, partners and internal product and engineering teams as a technical expert with deep domain expertise in the target use cases, system architecture, software stacks and performance optimization.

PREFERRED EXPERIENCE:
  • Strong expertise in processor micro-architecture definition and performance modeling
  • Strong expertise and hands-on experience working on computer architecture, GPU architecture, CPU and GPU micro-architecture, cache hierarchy, coherent memory sub-system, SoC internal interconnect, PCIe, integrated NIC and accelerators, performance modeling and performance analysis
  • Hands-on and strong expertise in performance analysis and Linux performance tools, e.g. perf, AMD uProf, Intel Vtune
  • Expertise and experience working with data plane and control plane architectures in networking devices is an advantage
  • Packet forwarding mechanisms using Open Vswitch, DPDK; security protocols like IPSec, TLS; offload with accelerators or smart NICs, P4; storage applications using SPDK, ISA-L; virtualization or container environment and orchestration like Kubernetes is an advantage
  • Experience in system design and architecture of networking products involving switching, routing and security, storage systems, wireless infrastructure equipment and telco applications is an advantage
  • Experience with Linux system programming (e.g. sockets, files, shared memory, multi-threaded programming/process synchronization.)
  • Good understanding and working knowledge of Ethernet and Layer 3/ Layer 4 network protocols such as TCP/IP, IPSec, TLS
  • Understanding of wireless 5G protocol is desired
  • Hands on experience with Linux networking stack is desired
  • Strong passion and experience in performance analysis, performance optimization, troubleshooting, debugging complex systems and possess excellent problem-solving techniques
  • Proficiency in C and at least one scripting language like shell script, python etc.
  • Experience with TCP/IP and knowledgeable with common standard IP protocols such as ARP, IP, ICMP, TCP, UDP, IPSec, TLS, etc
  • Experience with GPU programming is desired
  • Strong expertise in computer architecture, GPU architecture, PCIe, CXL, Ethernet is highly desired
  • Excellent verbal and written communication, and customer engagement skills.

ACADEMIC CREDENTIALS:
  • Bachelor's or Master's degree in Electrical Engineering or Computer Engineering

LOCATION: Austin, TX
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Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
This posting is for an existing vacancy.

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