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Deep Learning Performance Architect Jobs (NOW HIRING)

AT&T

Lead Performance Architect

Mesa, AZ

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Richardson, TX

$105K - $158K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Orlando, FL

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Charlotte, NC

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

Tenstorrent

Performance Architect, AI HW

$170K/yr

... deep learning workloads into architectural insight and measurable design tradeoffs. • Curious ... in high-performance AI systems. • Benchmark and analyze complex AI workloads across single and ...

AT&T

Lead Performance Architect

Atlanta, GA

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Miami, FL

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Chicago, IL

$105K - $158K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Tulsa, OK

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Cerritos, CA

$105K - $158K/yr

Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions ... Architect jobs earn between $105,600.00 - $158,400.00 USD Annual. Not to mention all the other ...

AT and T

Lead Performance Architect, Tulsa, OK

Tulsa, OK · On-site

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT and T

Lead Performance Architect, Miami, FL

Miami, FL · On-site

$94K - $141K/yr

Performance Architects focus on performance outcomes-not just training-by evaluating root causes ... Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions.

AT&T

Lead Performance Architect

Tustin, CA

$105K - $158K/yr

Collaborate with Learning Design and Delivery teams to develop and deploy performance solutions ... Architect jobs earn between $105,600.00 - $158,400.00 USD Annual. Not to mention all the other ...

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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 Jul 21, 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 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.
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 July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $167,842 per year, or $80.7 per hour.

Machine Learning Performance Engineer

Optiver

New York, NY

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago

Job description

Optiver is a seeking a Machine Learning Performance Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies.

What you'll do

As a Machine Learning Performance Engineer, your key responsibilities include:

  • Building scalable and robust training and inference pipelines for deep learning
  • Diving into internals of open-source deep learning frameworks and enhance their functionality
  • Identifying and eliminate performance bottlenecks
  • Collaborating closely with researchers and other engineers
  • Developing an in-depth understanding of trading systems

What you'll get

You'll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you'll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets.

In addition, you'll receive:

  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • A highly competitive compensation package
  • Global profit-sharing pool and performance-based bonus structure
  • 401(k) match up to 50%
  • Comprehensive health, mental, dental, vision, disability, and life coverage
  • 25 paid vacation days alongside market holidays
  • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more

Who you are

  • Strong knowledge of low-level GPU programming with CUDA, including Tensor Cores, cooperative groups, graphs, and warp-level intrinsics
  • Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.
  • Deep understanding of computer architecture
  • Experience in C++ and Python

Nice to have

  • Experience with JAX ecosystem (XLA, Flax, etc.)
  • Familiarity with GPU libraries and tools such as Triton, CUB, cuDNN, and cuBLAS
  • Linux system programming experience
  • Experience with large-scale distributed training
  • Contributions to open-source projects related to data science and machine learning

Who we are

At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilizing the market no matter the conditions. With a focus on continuous improvement, we prioritize safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe.

Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.

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