Internship Computer Vision Engineer information
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$13.46 - $15.76
5% of jobs
$15.76 - $18.05
7% of jobs
$20.30 is the 25th percentile. Wages below this are outliers.
$18.05 - $20.35
13% of jobs
$20.35 - $22.64
9% of jobs
The median wage is $24.49 / hr.
$22.64 - $24.93
19% of jobs
$24.93 - $27.23
18% of jobs
$27.80 is the 75th percentile. Wages above this are outliers.
$27.23 - $29.52
14% of jobs
$29.52 - $31.82
7% of jobs
$31.82 - $34.11
4% of jobs
$34.11 - $36.41
0% of jobs
$36.41 - $38.70
3% of jobs
How much do internship computer vision engineer jobs pay per hour?
As of Aug 19, 2026, the average hourly pay for internship computer vision engineer in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.
An Internship Computer Vision Engineer assists in developing and testing algorithms that allow computers to interpret and process visual information from the world, such as images and videos. They often work on tasks like object detection, image classification, and facial recognition using programming languages like Python and tools such as OpenCV or TensorFlow. Interns may also help collect and annotate datasets, run experiments, and analyze results under the guidance of senior engineers. This role is ideal for students or recent graduates seeking hands-on experience in the field of computer vision and artificial intelligence.
To thrive as an Internship Computer Vision Engineer, you need a solid background in computer science, mathematics, and image processing, usually demonstrated through coursework or relevant project experience. Familiarity with programming languages like Python or C++, frameworks such as OpenCV or TensorFlow, and knowledge of machine learning algorithms are commonly expected. Strong problem-solving abilities, attention to detail, and effective teamwork skills help you stand out in this collaborative and innovative field. These skills and qualities are crucial for developing, testing, and optimizing computer vision solutions that address real-world visual data challenges.
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