Computer Vision Engineer Salary: Your 2025 Guide

Computer vision is akin to a digital eye that enables machines to "see" and understand images. Backed by artificial intelligence (AI) and machine learning (ML), computer vision can sift through vast amounts of image and video data to identify and describe objects, faces, and scenes. 

Computer vision engineers—as the developers of the digital eye—play a vital role in shaping and advancing emerging technologies such as autonomous driving and medical imaging. Startups and tech giants, including Meta, Google, and Apple, actively seek computer vision engineers to foster innovation.

Learn more about this in-demand career, including the average computer vision engineer salary and the factors that influence it. 

What is a computer vision engineer?

A computer vision engineer specializes in designing programs and algorithms for detecting, categorizing, and tracking objects in image and video footage. In this role, you’ll also engage in extensive testing and troubleshooting to ensure the trustworthiness of computer vision systems. Other common work duties include: 

• Cleaning and preprocessing input data for machine learning models

• Training machine learning models for classification and automated decision-making

• Calibrating neural networks and deep learning models for designated vision tasks

• Gathering analytical data from computer vision algorithms

• Maintaining design and operational guides for computer vision systems

• Making certain computer vision systems adhere to relevant privacy and security regulations

How much does a computer vision engineer make?

The average annual pay for a computer vision engineer in the US ranges from $122,000 to $129,000, according to multiple job listing sites. Consider the base salary ranges provided by Payscale, Salary.com, Glassdoor, and Indeed [1, 2, 3, 4]. 

*All salary data as of February 2025

Factors that impact computer vision engineers’ salary

Your salary as a computer vision engineer can vary based on factors such as education, experience, skills, industry, location, and the company you work for. Understanding these elements can help you boost your earning potential.

Education 

Computer vision is part of the broader field of artificial intelligence. According to Zippia, artificial intelligence specialists with a bachelor’s degree earn approximately $170,704 per year [5]. A master's degree, however, offers a higher pay at around $196,643 per year. Most artificial intelligence specialists, about 63 percent, hold a bachelor's degree [5]. Common fields of study include computer science and computer engineering. 

Experience 

As your experience grows, so do your earnings. Consider the estimated average base pay you can earn based on your years of experience, according to Glassdoor [3].

• 0–1 year: $92,963

• 1–3 years: $100,731

• 4–6 years: $110,014

• 7–9 years: $121,005

• 10–14 years: $131,798

• 15 or more years: $144,426

Skills

A diverse skill set can open doors to various roles and responsibilities within an organization. By continually updating and refining your skills, you demonstrate a commitment to personal and professional growth, making you a more attractive candidate to potential employers. Payscale lists the following key skills for computer vision engineers and the average salaries that these skills bring [1]:

• Computer vision: $119,437

• Deep learning: $123,102

• Python: $110,222

• Machine learning: $116,129

• C++: $132,998

Industry 

Computer vision is gaining traction in a wide range of industries, including utilities, automotive, and manufacturing. For instance, a computer vision system engineered to inspect products on a manufacturing line can process thousands of items per minute, pinpointing subtle imperfections that might elude human detection. Strategically contributing to such high-value, profitable industries can help you boost your overall income. According to Glassdoor, IT and manufacturing are among the top-paying industries for computer vision engineers, offering the following median total salaries [3]:

• Information technology: $201,103

• Manufacturing: $150,388

Location

Earnings can differ significantly based on your geographical location, with some states, such as California, offering salaries that surpass the national average. If you’re willing to relocate, researching salaries specific to different locations can help you make an informed decision. Discover some of the top-paying cities for computer vision engineers in the US [4]:

• Sunnyvale, CA: $185,061

• Seattle, WA: $211,502 

• Menlo Park, CA: $210,192 

• San Francisco, CA: $169,418 

• San Jose, CA: $162,419

• Mountain View, CA: $159,791 

• New York, NY: $162,473

• Southfield, MI: $129,733 

• Dallas, TX: $118,626

Company 

Pay can differ between firms, depending on the scope of your training and responsibilities within an organization. Among the top-paying companies for computer vision engineers in the US are [3]:

• Cruise: $274,000–$387,000

• Meta: $269,000–$402,000

• Google: $247,000–$378,000

Job outlook

The job outlook for computer vision engineers is promising in the years ahead. The US Bureau of Labor Statistics (BLS) projects a 26 percent increase in employment prospects for computer and information research scientists between 2023 and 2033 [6]. The forecast translates to 3,400 job openings a year, on average, in that time frame [6]. 

Additionally, Grand View Research reports that the global computer vision market, valued at $19,82 billion in 2024, will expand at a compound annual growth rate (CAGR) of 19.8 percent from 2025 to 2030 [7]. Furthermore, thanks to technological advancements, an increasing number of industries, including education, health care, and consumer electronics, are embracing computer vision. As a result, computer vision will likely generate a large influx of job openings.

Getting started with computer vision on Coursera

Computer vision, in line with other forms of AI, helps automate tasks that mimic human abilities. Starting a career in this dynamic field requires honing a diverse range of skills. 

Get a headstart with the Machine Learning Specialization offered by Standford and DeepLearning.AI on Coursera. In this three-course series, you’ll master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng. You may also choose to further your learning with the IBM AI Engineering Professional Certificate, in which you’ll learn to build deep learning models and neural networks using Keras, PyTorch, and TensorFlow.