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Deep Learning Developer 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

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

$14/hr

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

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 · 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 agricultural environments.

Nvidia

Senior Deep Learning Engineer

Redmond, WA · On-site

$62 - $79.75/hr

We are now looking for a Senior Deep Learning Engineer!At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking ...

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 ...

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA

$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 ...

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Deep Learning Developer information

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How much do deep learning developer jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for deep learning developer in Seattle, WA is $43.75, according to ZipRecruiter salary data. Most workers in this role earn between $37.21 and $48.70 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
Deep Learning Developer jobs near you
Deep Learning Engineer

Deep Learning Engineer

Carbon Robotics

Seattle, WA • On-site

Other

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

Apply