How Computer Vision Engineers Develop the Eyes of AI

Jenni Kavanagh our consultant managing the role
Posting date: 3/19/2020 4:50 PM
Facial Recognition software. Autonomous vehicles. Drone delivery. Robotics in manufacturing. 3D Printing. No longer the stuff of science fiction, these advancements are at the heart of the next evolution in the digital age. Developments are not just being made in the tech hubs of Silicon Valley, Austin, or New York, but in the mid-West. Ann Arbor, Michigan home to the University of Michigan and not too far from where Henry Ford first introduced mass production with the help of automation has been advancing robotic technologies across a variety of fields. 

Giving machines their own set of eyes does require someone to ensure they have the right information to do their jobs. Enter the Computer Vision Engineer. It’s estimated this field will see a rise of 19% demand through 2026. It’s also a relatively small field with only 5,400 new job openings. So, like many professions, demand is high yet a shortage remains of those Data professionals with the right skillsets.

The Business of a Computer Vision Engineer


While there are a variety of roles within the field of Computer Vision, the role of Computer Vision engineer focuses on two areas. Those areas are:

  • Writing code in Python/C++
  • Integrate Data Visualization, image analysis, and imaging simulation controls

In addition to these areas, these scientists focus on research, implementation, reaching across teams both human and machine to help solve real world problems. And as important as knowledge and application theory are, it’s the hands-on experience which raises the bar for most employers and client companies. 

Using image recognition, machine learning, and segmentation can help machines learn to differentiate various images. Being able to “see” what the computer may see and correcting it to ensure it’s more like human vision takes a special skillset. This can include:

  • Computer Vision libraries
  • Database management
  • Component or object-oriented software
  • Analytical, logical, and critical thinking
  • Clear reasoning

It’s these skillsets along with a background in mathematics and computer languages like C++ which pave the Computer Vision engineer career path. 

The Future of Computer Vision 


The days of the generalist are long behind us. Now, more than ever, technologies like machine vision require a dedicated focus. With every field from healthcare to law enforcement to manufacturing utilizing these technologies, the future of Computer Vision performs a broader range of functions.  

In Ann Arbor, at the University of Michigan and in partnership with Ford Motor Company, advancements race through every field not the least of which is manufacturing. As they transition toward full automation using the Internet of Things and more autonomous processes, it’s even more important to ensure Computer Vision models understand what they’re “seeing.”

Computer Vision engineers will help to advance technologies which make machines easier to train and more easily figure out images better than they do now. Used in conjunction with other technologies like neural networks and other subsets of AI, machines will be able to see and interpret in the same way humans see and interpret. 

And as far as we’ve come, there remains more applications and benefits not yet explored. The possibilities are endless. Current and future advancements will pave the way for AI to be as human as we are bringing our once science fiction ideas to life. 

One Final Thought…


Though Computer Vision engineering can be drilled down to even more focused professions, the term itself is broad. But the specializations are basic with a demand for not only highly skilled professionals with the right educational background, but also hands-on experience. This detail is more important now than ever before, especially for Computer Vision teams seeking leadership roles who can take their applications to the next level and on a global scale. 

Some of the basic specializaitons include, but are not limited to:

  • Camera imaging geometry
  • Feature detection and matching
  • Image classification and scene analysis

In the wake of work-from-home policies, remote working, and the shifting landscape of working outside the office, technology careers are prime opportunities to both gain increased knowledge in your chosen field or begin your career path. 

If you’re ready to take the next step in your career, we may be able to help. Take a look at our current vacancies or get in touch with one of our expert consultants to learn more.  

For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  

For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

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