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Deep Learning Engineer Jobs in Seattle, WA (NOW HIRING)

Sr. Machine Learning Engineer 4

Seattle, WA

$118K - $163K/yr

Develop, evaluate, and deploy ML models using classical, deep learning, and GenAI approaches ... Mentor junior engineers and help grow the team's technical depth. What You Need to Succeed Required ...

They are seeking a highly-motivated, creative, and knowledgeable Machine Learning Engineer to help ... modern deep learning frameworks, like PyTorch or JAX • Experience with Python scientific ...

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Showing results 1-20

Deep Learning Engineer information

See Seattle, WA salary details

$43.2K

$131.9K

$217.9K

How much do deep learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for deep learning engineer in Seattle, WA is $131,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $172,400.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are popular job titles related to Deep Learning Engineer jobs in Seattle, WA? For Deep Learning Engineer jobs in Seattle, WA, the most frequently searched job titles are:
Infographic showing various Deep Learning Engineer job openings in Seattle, WA as of June 2026, with employment types broken down into 10% Internship, 71% Full Time, and 19% Contract. Highlights an 95% In-person, and 5% Hybrid job distribution, with an average salary of $131,855 per year, or $63.4 per hour.
Senior Deep Learning Performance Architect

Senior Deep Learning Performance Architect

Nvidia

Redmond, WA

$187K/yr

Full-time

Posted 26 days ago


Job description

We are now seeking a Senior Deep Learning Performance Architect! NVIDIA is looking for outstanding Performance Architects with a background in performance analysis, performance modeling, and AI/deep learning to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

What you'll be doing:

  • Develop innovative architectures to extend the state of the art in deep learning performance and efficiency

  • Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites

  • Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications

  • Evaluate PPA (performance, power, area) for hardware features and system level architectural trade-offs. Develop high level simulators in C++/Python

  • Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

What we need to see:

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

  • 6+ years of relevant meaningful work experience

  • Strong background in GPU or Deep Learning ASIC architecture for distributed training and/or inference spanning multi-chip/multi-node

  • Experience with performance modeling, architecture simulation, profiling, and analysis

  • Solid foundation in machine learning and deep learning. Understanding of modern transformer-based architectures and their performance at scale.

  • Strong programming skills in Python, C, C++

Ways to stand out from the crowd:

  • Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT)

  • Familiarity with advanced optimizations and SW/HW co-design in LLM training and inference

  • Exposure to using AI to accelerate SW engineering

  • Demonstration of self-motivation and creative / critical thinking

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as "the AI computing company", NVIDIA wants you! Come, join our Deep Learning Architecture team, where you can help build real-time, efficient computing platforms driving our success in this exciting and rapidly 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 June 7, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Nvidia logo

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