Computer Vision Engineer Career Guide
A computer vision engineer, also known as a machine vision engineer, is a highly specialized professional with at least a bachelor’s degree in computer science or a related field and knowledge of programming languages like C++.
The overall concept of this field is that a machine or computer can see as a human being can. The goal of a computer vision engineer is to create programs that can not only see visual information, but also interpret it.
As computers and sensors grow increasingly sophisticated, specializations like computer vision engineering are growing along with them.
Computer vision engineers work with visual data. This information can come in various ways, such as through video feeds, digital signals, or analog images that the computer digitizes.
UPC readers in supermarkets are among the earliest examples of tools employing computer vision concepts. They read bar codes and use that information to determine which product the cashier is swiping. QR codes are a more recent example of this.
Within this context, a computer vision engineer applies cutting-edge ideas in the field of computer vision to real-world problems. Often, computer vision projects involve collecting and transforming a large amount of data via machine learning systems for a specific purpose.
Much of a computer vision engineer’s time is spent doing research and implementing research results into machine learning systems to build solutions for their clients or employer. Computer vision engineers closely collaborate with other professionals to build hardware and software that uses visual data to solve a specific problem or complete a specific task.
To do their job well, computer vision engineers require plenty of experience in various areas such as computer science, machine learning, image recognition, and applied mathematics.
Computer vision engineers often find clever ways to incorporate artificial intelligence into different areas. Some of the applications that use computer vision extensively include:
- Image enhancement. This has to do with the computers’ ability to zoom into blurred images and sharpen them.
- Image search: This growing feature in search engines allows users to search pictures rather than text. Search engines such as Google use computer vision to recognize the images and search for similar ones in the database.
- Content moderation. With more social media platforms supporting visual data than ever before, it is important to ensure that inappropriate content does not make it to end-users. These platforms use computer vision tools to look through all the photos posted daily to find images that do not meet policy requirements.
- Facial recognition. Computer vision software allows platforms like Tinder and Facebook to recognize your face. It is similarly used in law enforcement and government agencies and for security features, such as unlocking your phone.
- Self-driving cars. With self-driving cars becoming more widespread, computer vision allows these vehicles to identify different objects on the road for safety and navigation.
An engineer’s work is as varied as the contexts within which computer vision is applicable. There are, however, a few general tasks that most computer vision engineers will regularly carry out:
- Develop, test, debug, deploy, and maintain computer vision algorithms and hardware for different environments.
- Develop automated vision algorithms, especially for work with robots and autonomous hardware systems.
- Gather and optimize analytics from computer vision algorithms to improve their performance.
- Study real-world problems and propose practical, efficient, and creative solutions to those problems.
- Build technical documentation for computer vision systems for end-users to understand how these systems work and how to use them.
- Manage large and small-scale computer vision projects, define project requirements, prepare budgets, and run technical development teams.
Of course, depending on the specific domain within which a particular computer vision engineer works, there might be more tasks and responsibilities.
Considering the technical demands of this profession, a strong educational background is necessary to get your foot in the door. You should have at least a bachelor’s degree in computer science or some other IT-related degree.
You should also have experience and demonstrable skills in programming with languages like Java, C++, or Python, and in working with machine and deep learning libraries like TensorFlow and PyTorch. More often than not, computer vision engineers don’t start in this field. They take on a related junior role in software engineering or data science. Then, after gathering experience and building their educational qualifications, they may move on to a computer vision career.
Computer Science – B.S.
Problem solvers and math lovers needed! Your task: ...
Problem solvers and math lovers needed! Your...
Problem solvers and math lovers needed! Your task:
Lay the groundwork for the computing breakthroughs that will enable tomorrow's technologies.
- Time: 67% of graduates in similar programs finish within 30 months.
- Tuition and fees: $3,985 per 6-month term.
- Transfer: Your previous college coursework and existing certifications may waive course requirements, helping you finish even faster.
You'll have the opportunity to earn these certifications:
- Linux Essentials
- Axelos ITIL Foundation
Professionals who need the skills a computer science degree provides include computer systems analysts, computer programmers, artificial intelligence specialists, software engineers, machine learning engineers, and more.
No need to wait for spring or fall semester. It's back-to-school time at WGU year-round. Get started by talking to an Enrollment Counselor today, and you'll be on your way to realizing your dream of a bachelor's or master's degree—sooner than you might think!
To thrive in this career, you will need a variety of skills:
- Technical skills. This includes proficiency in computer science concepts, as well as machine learning libraries and tools, such as TensorFlow, PyTorch, MatLab, Point Cloud Library, and OpenCV. You will learn many of these as part of your degree course or certification.
- Analytical skills. A lot of your work will involve dealing with very large data sets, crunching the numbers, and trying to make sense of them. To excel at this, you will need to have excellent analytical abilities.
- Problem-solving skills. Computer vision is at the frontier of computer science research, which means you will often deal with novel problems. You should be good at breaking down large and complex problems into smaller and more manageable ones.
- Communication skills. You will regularly have to collaborate with others, including upper management. Good communication skills will enable you to understand client requirements and communicate your progress on projects.
Other skills may vary depending on the industry in which you work.
How Much Does a Computer Vision Engineer Make?
According to the U.S. Bureau of Labor Statistics, computer vision engineers fall under the category of computer and information research scientists. The median pay for this group was $126,830 in May 2020. The top 10% made more than $194,430, while the bottom 10% made less than $72,210.
Pay is mainly determined by your level of education, years of experience, demonstrable skills, employer, and location. Those with a higher computer science degree can typically expect to earn more.
What Is the Projected Job Growth?
According to the U.S. Bureau of Labor Statistics, employment opportunities for computer and information research scientists should grow by 15% from 2019 to 2029. This is much higher than the national average for all professions.
With greater demand for industry-leading technological tools, there will be a greater need for professionals capable of coming up with creative tech solutions to real-world problems, including computer vision engineers.
Where do Computer Vision Engineers Work?
Computer vision engineers work in a variety of environments:
-Social media platforms
-Government defense agencies
-Point-of-sale device makers
-IoT manufacturing agencies
-Self-driving car manufacturers
-Medical technology companies
Basically, in any place where computer vision might solve some critical issues, you can expect to find a specialist working on a solution.