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Deep Learning Performance Architect Jobs (NOW HIRING)

Nvidia

Senior CPU Performance Architect

Santa Clara, CA · On-site

$196.10K/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 ...

Sandisk

Performance Architect

Milpitas, CA · On-site

$190.40K/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 ...

Sandisk

Performance Architect

Milpitas, CA · On-site

$136.54K - $226.15K/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 ...

Sandisk

Performance Architect

Milpitas, CA · On-site

$190.40K/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

$147.40K - $272.10K/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 ...

Apple

Systems Performance Architect

Beaverton, OR

$147.40K - $272.10K/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 ...

Nvidia

Senior CPU Performance Architect

Hillsboro, OR · On-site

$181.90K/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 · On-site

$165.50K/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

$196.10K/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 May 31, 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, 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 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 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.

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
Principal Performance Architect

Principal Performance Architect

Advanced Micro Devices, Inc

Austin, TX • On-site

$175K/yr

Full-time

Posted 27 days ago

Advanced Micro Devices rating

7.8

Company rating: 7.8 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

53rd of 137 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 AMD's Embedded Business Unit, you will define and shape the next generation of x86 SoCs through deep pre-silicon performance modeling, architecture exploration, and competitive analysis.
THE PERSON:
You will work across architecture, design, firmware, and post-silicon teams to lead and influence decisions that directly determine product competitiveness and customer experience. This is a highly technical, forward-looking, and business-critical role.
KEY RESPONSIBILITIES:
  • Lead pre-silicon performance architecture, including workload-driven performance projections across CPU, GPU, NPU, memory, interconnect, and I/O subsystems.
  • Build and refine cycle-accurate, trace-based, and analytical performance models for emerging SoC architectures.
  • Drive competitive performance projections against products from Qualcomm, Apple, NVIDIA, Intel, MediaTek, and others.
  • Analyze micro-architecture trade-offs (NoC, caches, memory controllers, coherency fabrics) to optimize perf/power/area; write clear recommendations to architecture.
  • Own performance bottleneck analysis, microarchitectural what-if evaluations, and trade-off recommendations.
  • Define performance KPIs, PnP assumptions, and workload suites for early feasibility modeling.
  • Lead post-silicon performance correlation, root-cause gaps, and update pre-silicon models to improve fidelity.
  • Work closely with product management, architecture, and SoC design teams to influence product definition, PPA targets, and roadmap decisions.

PREFERRED EXPERIENCE:
  • Strong understanding of CPU/GPU microarchitecture, memory hierarchy, and SoC interconnects.
  • Hands-on experience with performance simulators (gem5, proprietary, trace-driven frameworks).
  • Deep experience with workloads-SPEC, industry vertical benchmarks, synthetic stressors.
  • Strong scripting skills (Python, C++, MATLAB).
  • Experience with ML, automotive, edge compute, industrial workloads.
  • Familiarity with firmware, compilers, DV, and RTL design concepts.

ACADEMIC CREDENTIALS:
  • MS/PhD in EE/CE/CS with experience in performance architecture or modeling experience.

LOCATION:
Austin, TX or US Remote
This role is not eligible for visa sponsorship.
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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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