Computer Vision Engineer Salary in 2023
💰 The median Computer Vision Engineer Salary in 2023 is USD 210,000
✏️ This salary info is based on 21 individual salaries reported during 2023
Salary details
The average Computer Vision Engineer salary lies between USD 175,000 and USD 235,000 globally. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.
- Job title
- Computer Vision Engineer
- Experience
- all levels
- Region
- global/worldwide
- Salary year
- 2023
- Sample size
- 21
- Top 10%
-
- Top 25%
-
- Median
-
- Bottom 25%
-
- Bottom 10%
-
All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Salary trend
Top 20 Job Tags for Computer Vision Engineer roles
The three most common job tag items assiciated with Computer Vision Engineer job listings are Computer Vision, Python and Machine Learning. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:
Computer Vision | 90 jobs Python | 77 jobs Machine Learning | 68 jobs Deep Learning | 66 jobs Engineering | 65 jobs Computer Science | 63 jobs PyTorch | 47 jobs TensorFlow | 46 jobs Research | 44 jobs OpenCV | 32 jobs Pipelines | 29 jobs Robotics | 25 jobs PhD | 23 jobs Docker | 23 jobs Testing | 22 jobs CUDA | 21 jobs Architecture | 20 jobs Linux | 19 jobs Classification | 18 jobs AWS | 16 jobsTop 20 Job Perks/Benefits for Computer Vision Engineer roles
The three most common job benefits and perks assiciated with Computer Vision Engineer job listings are Career development, Team events and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:
Career development | 61 jobs Team events | 27 jobs Health care | 25 jobs Startup environment | 23 jobs Flex hours | 20 jobs Equity / stock options | 15 jobs Competitive pay | 15 jobs Flex vacation | 14 jobs Medical leave | 9 jobs Parental leave | 8 jobs 401(k) matching | 7 jobs Wellness | 7 jobs Insurance | 7 jobs Salary bonus | 7 jobs Relocation support | 6 jobs Conferences | 5 jobs Unlimited paid time off | 5 jobs Snacks / Drinks | 4 jobs Home office stipend | 4 jobs Fitness / gym | 3 jobsSalary Composition for a Computer Vision Engineer
The salary for a Computer Vision Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the compensation package is composed of:
-
Base Salary: This is the fixed component and usually constitutes the majority of the total compensation. In regions like the San Francisco Bay Area or New York, the base salary might be higher due to the cost of living and demand for tech talent.
-
Bonus: Many companies offer annual performance bonuses, which can range from 10% to 20% of the base salary. The bonus structure can vary widely depending on the company's performance and individual contributions.
-
Equity/Stock Options: Especially in tech companies and startups, equity can be a significant part of the compensation package. This can include stock options or restricted stock units (RSUs), which vest over a period of time.
-
Other Benefits: Additional remuneration might include health insurance, retirement plans, and other perks like wellness programs, transportation allowances, or educational reimbursements.
Steps to Increase Salary
To increase your salary from the position of a Computer Vision Engineer, consider the following strategies:
-
Specialize Further: Gain expertise in niche areas within computer vision, such as 3D vision, autonomous systems, or deep learning, which are in high demand.
-
Pursue Advanced Roles: Aim for senior or lead positions, such as a Senior Computer Vision Engineer or a Computer Vision Team Lead, which come with higher pay.
-
Expand Your Skill Set: Learn complementary skills like machine learning, data science, or software engineering to increase your value to employers.
-
Network and Build a Personal Brand: Attend industry conferences, contribute to open-source projects, and publish research to enhance your reputation in the field.
Educational Requirements
Most Computer Vision Engineer positions require at least a bachelor's degree in a relevant field such as:
- Computer Science
- Electrical Engineering
- Mathematics
- Physics
However, many employers prefer candidates with a master's degree or a Ph.D., especially for research-intensive roles.
Helpful Certifications
While not always required, certain certifications can enhance your profile:
- Deep Learning Specialization by Coursera, offered by Andrew Ng
- TensorFlow Developer Certificate by Google
- AWS Certified Machine Learning – Specialty for those working with cloud-based solutions
These certifications demonstrate proficiency in key technologies and methodologies used in computer vision.
Experience Requirements
Typically, employers look for candidates with:
Want to contribute?
📝 Submit your salary info
Enter your own salary data for the current or past work year. It's quite simple and doesn't take more than a minute to fill out.
Go to salary survey📢 Share our salary survey
Share our "in-less-than-a-minute survey" with others working in the field of AI, ML, Data Science. The more data we have the better for everyone.
💾 Download the data
All collected information will be updated into a public dataset regularly and provided as a download free for anyone to use.
Go to download page🚀 Search for jobs & talent
If you're thinking about a career change or want to hire fresh talent quickly check out the jobs page.
Go to frontpageAbout this project
We collect salary information anonymously from professionals and employers all over the world and make it publicly available for anyone to use, share and play around with.
Our goal is to have open salary data for everyone. So newbies, experienced pros, hiring managers, recruiters and also startup founders or people wanting to switch careers can make better decisions.