Computer Vision Engineer: Facts, Skills, and Next Paths

A Computer Vision Engineer builds systems that enable machines to interpret and act on visual data from cameras, sensors, and video feeds. Day to day, you design and train deep learning models for tasks like object detection, image classification, and real-time video analysis, then deploy those models to production—often on edge devices or in cloud environments.

Core responsibilities include curating and managing large image and video datasets, refining annotation workflows, and collaborating with cross-functional teams to integrate vision models into industrial or enterprise systems. For example, at Amazon you would develop models to improve workplace safety across global operations, while at Mentium you would optimize a deep learning library for ultra-low-power hardware. The role typically reports to a lead engineer or AI team lead and works closely with software engineers, data scientists, and domain experts.

The median salary for Computer Vision Engineers is approximately $232,500. The most requested skills in current job postings are Machine Learning & Deep Learning (90%), Computer Vision (80%), and Python or R (50%), with Version Control, Data Integration, CI/CD, Documentation, C++, and Data Quality also commonly required.