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Temporary Computer Vision Deep Learning Engineer Jobs

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for ... for computer vision in agricultural environments • Own model optimization and deployment ...

Carbon Robotics

Deep Learning Engineer

Seattle, WA · On-site

As a Deep Learning Engineer, you will design, develop, and deploy deep learning systems for ... for computer vision in agricultural environments • Own model optimization and deployment ...

NBCUniversal

Deep Learning Engineer

Manhattan, NY · On-site

They are seeking a Deep Learning Engineer to implement algorithms that integrate computer vision and graphics, focusing on transforming large datasets into high-fidelity content. Responsibilities ...

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All JobsComputer Vision Deep Learning Engineer JobsTemporary Computer Vision Deep Learning Engineer Jobs

Temporary Computer Vision Deep Learning Engineer information

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$48.5K

$121.5K

$137.5K

How much do temporary computer vision deep learning engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for temporary computer vision deep learning engineer in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Computer Vision Deep Learning Engineer vs Computer Vision Engineer?

AspectTemporary Computer Vision Deep Learning EngineerComputer Vision Engineer
CredentialsBachelor's or Master's in CS, AI, or related; experience with deep learning frameworksBachelor's or Master's in CS, AI, or related; experience with computer vision tools
Work EnvironmentProject-based, short-term contracts, often in tech or research firmsFull-time, ongoing roles in tech companies, startups, or research labs
Industry UsageCommon in consulting, research projects, or temporary assignmentsStandard role in product development, AI solutions, and software engineering

The main difference is that a Temporary Computer Vision Deep Learning Engineer works on short-term projects focusing on deep learning techniques for computer vision, while a Computer Vision Engineer typically holds a permanent position involved in ongoing development of computer vision applications. The temporary role emphasizes flexibility and project-specific skills, whereas the full-time role involves continuous integration into a company's long-term projects.

More about Temporary Computer Vision Deep Learning Engineer jobs
What cities are hiring for Temporary Computer Vision Deep Learning Engineer jobs? Cities with the most Temporary Computer Vision Deep Learning Engineer job openings:
What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs? The most popular types of Computer Vision Deep Learning Engineer jobs are:
What states have the most Temporary Computer Vision Deep Learning Engineer jobs? States with the most job openings for Temporary Computer Vision Deep Learning Engineer jobs include:
What job categories do people searching Temporary Computer Vision Deep Learning Engineer jobs look for? The top searched job categories for Temporary Computer Vision Deep Learning Engineer jobs are:
Temporary Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Temporary Computer Vision Deep Learning Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 82% Physical, 1% Hybrid, and 17% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
Deep Learning Engineer

Deep Learning Engineer

Carbon Robotics

Seattle, WA • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
Carbon Robotics is an innovative company focused on revolutionizing agriculture with advanced robotics and AI technology. 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.
Responsibilities:
• 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
Qualifications:
Required:
• 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
• 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)
Preferred:
• 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
Company:
Carbon Robotics is revolutionizing agriculture with AI and robotics to reduce costs and increase yields Founded in 2018, the company is headquartered in Seattle, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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