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Computer Vision Image Processing Jobs (NOW HIRING)

Apple

Camera Architect

Sunnyvale, CA · On-site

... computer vision, image quality metrics, image sensor and pixel fundamentals, image processing pipeline Preferred Qualifications MS, or PhD in Physics, Engineering, Computer Science, Imaging Science ...

United IT

Computer Vision Engineer

Fremont, CA · On-site

$122K - $143K/yr

As a Computer Vision Software Engineer, your tasks are focused on developing and testing image processing algorithms used in our robotic systems. The work covers the entire pipeline from data ...

United IT Solutions

Computer Vision Engineer

Fremont, CA · On-site

$122K - $143K/yr

As a Computer Vision Software Engineer, your tasks are focused on developing and testing image processing algorithms used in our robotic systems. The work covers the entire pipeline from data ...

Apple

Camera Architect

Sunnyvale, CA

$147K - $272K/yr

... computer vision, image quality metrics, image sensor and pixel fundamentals, image processing pipeline Experience defining camera metrics and specifications through product goals, user studies and ...

Apple

Camera Architect

Sunnyvale, CA

$181K - $272K/yr

... computer vision, image quality metrics, image sensor and pixel fundamentals, image processing pipeline Experience defining camera metrics and specifications through product goals, user studies and ...

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Computer Vision Image Processing information

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How much do computer vision image processing jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for computer vision image processing in the United States is $20.85, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $23.32 per hour, depending on experience, location, and employer.

What are some typical challenges faced by professionals in Computer Vision Image Processing roles, and how can they be addressed?

Professionals in Computer Vision Image Processing often encounter challenges such as dealing with noisy or incomplete data, ensuring real-time performance, and adapting models to work across diverse environments and lighting conditions. Addressing these challenges typically involves using data augmentation techniques, optimizing algorithms for efficiency, and leveraging transfer learning to improve model robustness. Collaboration with cross-functional teams, such as hardware engineers and software developers, is also vital to ensure solutions are both accurate and deployable in real-world applications.

What is the difference between Computer Vision Image Processing vs Image Analysis Specialist?

AspectComputer Vision Image ProcessingImage Analysis Specialist
Required CredentialsBachelor's or higher in Computer Science, Electrical Engineering, or related fields; knowledge of programming and algorithmsBachelor's or higher in Data Science, Computer Science, or related fields; expertise in image data interpretation
Work EnvironmentResearch labs, tech companies, manufacturing, healthcareResearch institutions, tech firms, healthcare, security
Industry UsageDeveloping algorithms for object detection, recognition, and image enhancementInterpreting image data for insights, diagnostics, or decision-making

Computer Vision Image Processing focuses on developing algorithms to manipulate and analyze images, while Image Analysis Specialists interpret image data to extract meaningful insights. Both roles require similar educational backgrounds and often work in overlapping industries, but their core objectives differ: processing versus analysis.

What is computer vision image processing?

Computer vision image processing is a field of computer science that focuses on enabling computers to interpret and analyze visual information from the world, such as images and videos. It involves applying algorithms and techniques to process, enhance, and extract meaningful information from digital images. Common applications include object detection, facial recognition, image classification, and medical image analysis. The goal is to automate tasks that the human visual system can perform, making it possible for machines to 'see' and understand visual data.

What are the key skills and qualifications needed to thrive as a Computer Vision Image Processing Specialist, and why are they important?

To thrive as a Computer Vision Image Processing Specialist, you need strong foundations in mathematics, programming (especially Python or C++), and a relevant degree in computer science, engineering, or a related field. Familiarity with technical tools like OpenCV, TensorFlow, PyTorch, and experience with image processing libraries and frameworks are crucial, as are certifications in machine learning or deep learning. Analytical thinking, creativity, and effective problem-solving help individuals excel in developing and optimizing complex visual algorithms. These skills are essential for accurately interpreting visual data, driving innovation, and delivering robust solutions across various industries.
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Computer Vision Image Processing jobs near you
Image Processing Engineer / SLAM Algorithm Engineer

Image Processing Engineer / SLAM Algorithm Engineer

Position Imaging, Inc.

Portsmouth, NH

Other

Posted 10 days ago

Job description

Company Description

Highly accurate wireless tracking in 3D space, enabling large-scale, immersive augmented and virtual reality experiences without the use of any markers.

Job Description

Design and develop real 3D image processing algorithms using SLAM for Augmented and Virtual Reality applications.

Qualifications

Expert in 3D computer vision, with specific focus on Visual SLAM.

Experience in statistically optimal filtering, such as the Kalman filter.

Past success with SLAM algorithm development.

Computer vision knowledge, reconstruction, feature detection, segmentation and classification.

C/C++ programming skills.

Familiarity with OpenCV or similar.

Experience with IMUs and mono/RGB sensors.

Feature tracking and/or Structure From Motion experience.

Strong communication skills


Additional Information

Education Requirements: Master's degree in Computer Science, PhD a plus

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