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Deep Learning Jobs in Seattle, WA (NOW HIRING)

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

Deep Learning Engineer As a Deep Learning Engineer at Carbon Robotics, you will contribute to designing, developing, and deploying novel deep learning systems that power our autonomous laser weeding ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for autonomous laser weeding robots, ensuring high performance and scalability in agricultural environments.

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for autonomous laser weeding robots, ensuring high performance and reliability in agricultural environments.

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for autonomous laser weeding robots, ensuring high performance and scalability in real-world applications.

Carbon Robotics

Deep Learning Engineer

Seattle, WA

$140K - $220K/yr

YouTube | X | Instagram | LinkedIn | News Deep Learning Engineer As a Deep Learning Engineer at Carbon Robotics, you will contribute to designing, developing, and deploying novel deep learning ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

$140K - $220K/yr

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YouTube | X | Instagram | LinkedIn | News Deep Learning Engineer As a Deep Learning Engineer at Carbon Robotics, you will contribute to designing, developing, and deploying novel deep learning ...

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling ...

NVIDIA

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

They are seeking a Deep Learning Compiler Engineer to analyze deep learning networks and develop compiler optimization algorithms, collaborating with various teams to enhance deep learning software ...

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How much do deep learning jobs pay per year?

As of Aug 16, 2026, the average yearly pay for deep learning in Seattle, WA is $95,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,900.00 and $158,200.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a deep learning professional?

As a Deep Learning professional, your day-to-day tasks often include designing and training neural network models, preprocessing and analyzing large datasets, and evaluating model performance using various metrics. You may also participate in research activities, document your results, and collaborate with data scientists, engineers, or product teams to deploy machine learning solutions. Regular meetings for project updates, code reviews, and brainstorming sessions are common, as is staying updated on advances in the field. This dynamic environment offers both individual and team-based work, providing continuous learning and the opportunity to solve complex, real-world problems.

What is a deep learning job?

A Deep Learning job involves designing, developing, and optimizing neural networks to solve complex problems such as image recognition, natural language processing, and autonomous systems. Professionals in this field work with large datasets, neural network architectures, and frameworks like TensorFlow or PyTorch. They collaborate with data scientists, engineers, and researchers to improve model accuracy and efficiency. Deep Learning roles typically require strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration.

What are the key skills and qualifications needed to thrive in a deep learning position?

To thrive in Deep Learning, you need a solid understanding of machine learning theory, neural networks, mathematics (especially linear algebra and probability), and programming skills, typically backed by a degree in computer science, mathematics, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with data preprocessing, and optionally industry-recognized certifications are advantageous. Strong analytical thinking, problem-solving skills, and the ability to communicate findings clearly are crucial soft skills. These abilities enable the design, implementation, and optimization of effective deep learning solutions in real-world applications.

What are the most commonly searched types of Deep Learning jobs in Seattle, WA?

The most popular types of Deep Learning jobs in Seattle, WA are:

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For Deep Learning jobs in Seattle, WA, the most frequently searched job titles are:

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The top searched job categories for Deep Learning jobs in Seattle, WA are:

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Deep Learning jobs near you
Infographic showing various Deep Learning job openings in Seattle, WA as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $95,464 per year, or $45.9 per hour.

Deep Learning Engineer

Carbon Robotics

Seattle, WA • On-site

Full-time

Re-posted yesterday

Job description

Deep Learning Engineer 

As a Deep Learning Engineer at Carbon Robotics, you will contribute to designing, developing, and deploying novel deep learning systems that power our autonomous laser weeding robots in the field. 

What You'll Do

  • Lead the design and execution of experiments to develop and validate novel deep learning architectures for computer vision in agricultural environments
  • Own model optimization and deployment pipelines - ensuring high performance, reliability, and scalability across operational field deployments
  • Drive end-to-end ML workflows from data strategy and pipeline design through evaluation and production deployment
  • Define best practices for experimentation, documentation, and model evaluation within the team
  • Partner with Engineering and Product Management to scope, prioritize, and deliver high-impact features
  • Mentor and provide technical guidance to mid-level and junior engineers
  • Communicate model architecture decisions, tradeoffs, and performance results to both technical and non-technical audiences

Knowledge, Skills & Abilities

  • 2-4 years of professional experience designing and implementing novel deep learning architectures for production computer vision systems
  • Deep understanding of foundational deep learning mathematics and the ability to apply first-principles thinking to architecture decisions
  • Hands-on experience working across the software stack, including sensor integration and web services, ideally within a robotics or autonomous field equipment platform
  • Experience with deep learning frameworks, particularly PyTorch, and proficiency in C++ for performance-critical model development and deployment
  • Proven track record taking ML projects from inception through business impact - including data strategy, pipeline development, experimentation, and deployment at scale
  • Strong expertise in modern object detection techniques (vision transformers, anchor-free detectors, embeddings, and beyond)
  • Experience in autonomous driving or ADAS is a plus - background in perception pipelines, sensor fusion, or real-time inference in outdoor or unstructured environments is highly valued
  • Comfort navigating ambiguity and making principled technical decisions in rapidly evolving technical landscapes
  • Strong verbal and written communication skills - able to explain complex model behavior and tradeoffs to non-technical staff and customers
  • Experience mentoring engineers and contributing to team technical culture

Requirements

  • 2-7 years of experience in deep learning model optimization and deployment
  • BS+ in Computer Science, Machine Learning, or a related field (or equivalent experience)


In Office Requirements

  • We're a collaborative, in-person team - this role is based in our Seattle office with at least 4 days per week on-site

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