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

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 ...

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 ...

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.

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.

Deep Learning Engineer

Seattle, WA · On-site

$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 ...

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.

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 ...

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 ...

Deep knowledge of math, probability, statistics, and algorithms * Ability to write robust code in Python, Java, and R * Familiarity with machine learning frameworks (like Keras or PyTorch) and ...

Deep knowledge of math, probability, statistics, and algorithms * Ability to write robust code in Python, Java, and R * Familiarity with machine learning frameworks (like Keras or PyTorch) and ...

Required : • 3-5 years of proven experience as a Machine Learning Engineer or a similar role • Strong experience with Deep Learning • Understanding of data structures, data modeling, and ...

Machine Learning Engineer

Seattle, WA · On-site

$93K - $125K/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 ...

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Deep Learning Engineer information

See Seattle, WA salary details

$43.3K

$131.9K

$218.1K

How much do deep learning engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for deep learning engineer in Seattle, WA is $131,931.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $172,500.00 per year, depending on experience, location, and employer.

What is a deep learning engineer?

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 skills and qualifications does a deep learning engineer need?

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 does a deep learning engineer do?

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.

Infographic showing various Deep Learning Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $131,931 per year, or $63.4 per hour.

Full-time

Re-posted 26 days ago


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