do-not-give-up

This post has been inspired by a question someone asked in a forum. This person was a new but competent programmer who was trying to move into Computer Vision (CV) in the industry. However, he rightly noticed that “most of the job requirements [in computer vision] are asking for a PhD”.

Indeed, this is true. And because of this, finding a job in computer vision in the industry is very difficult. Mainly because computer vision (e.g. video analytics) hasn’t caught on yet as a meaningful source of data or income for companies. I think it will sooner or later (more on this in a future post) but the reality is that such jobs are rare and hence why companies can afford to advertise and be picky for people with a PhD.

So, if you’re in a situation where you can’t land a job in CV and especially if you’re without a PhD, don’t give up. Computer vision is a fascinating field to work in and it will only get bigger with time. It’s worth fighting on.

Here are three things you can do to improve your chances of landing that job that you really want.

Read Books, Tutorials, Publications, and Blogs

This is obvious but needs to be said. Keep reading up on the field, keep fine-tuning your skills and knowledge in CV. You need to show your potential employer that you know the field of CV exceptionally well. Read important books that are or have been published. Some you can find in your library, some come in PDF format. For example, Neural Networks and Deep Learning is a great book on the hot topic of neural networks that is available online free of charge.

Work through the tutorials available on the OpenCV page. There’s plenty there on machine learning, photo processing, object detection, etc. to keep you busy for months! The idea is to get so good at CV to be able to instantly see a solution to an image/video processing problem. You need to shine at those job interviews.

Follow blogs on Computer Vision. Two of my favourite are PyImageSearch and Learn OpenCV. These guys are regularly posting stuff that will fascinate anybody with a passion for Computer Vision. In fact, PyImageSearch is so well-written that it put me off from starting this blog for a while.

Consider also looking into academic publications. These can be daunting, especially if you don’t have a background in research. But focus initially on the seminal papers (more on this in a future post) and try to get the gist of what the scientists are saying. You can usually pick up small bits and pieces here and there and implement simplified versions of them.




Side Projects

One thing that did get me a lot of attention were my side projects. Side projects show people where your passions lie. And passion is something that a lot of companies are looking for. Believe me, if you came to my company and I was asked to interview you to join the Computer Vision team, your side projects would be one of the first things I’d be looking at.

So, get stuck into a few of these to show that you love the area and you do this kind of stuff for fun. Get a Raspberry PI going with a camera and build your own security system via motion detection, for example. Or get a drone for your Raspberry Pi and camera and be creative with it. Then list these side projects at the end of your CV. If you’re truly passionate about Computer Vision, you will get noticed sooner or later.

Branch out into other areas of Artificial Intelligence

What I decided to do when my job hunting wasn’t going too well was to aim for jobs in other areas of AI rather than just Computer Vision. It involved me having to pick up additional knowledge in fields I wasn’t too familiar with (e.g. Robotic Process Automation) but the amount of jobs in these areas is much larger. This tactic proved successful for me. I ended up picking a company (yes, I was spoilt for choice in the end!) that had interesting clients and it was only a matter of time before opportunities for computer vision projects came along that we were all pushing for.

An Inspirational Story

If you are feeling down about your job searching or if you’re wondering whether CV is a viable place to aim for in the job market, here is a truly inspirational story out of India (from PyImageSearch – I told you it was a well-written blog!). It’s about a fellow who really wanted to work in CV but was at a disadvantage because he came from a low-income family. But he didn’t give up and put the hard work in. Today he is working on AI solutions for drones for a company in India. Moreover, with his salary he can support his family, has paid off all his debts, and is working in a field he absolutely loves!

Summary

Finding a job in Computer Vision is difficult. Most companies are advertising for people with a PhD. But there are things you can do to boost your chances of landing that job you really want. For example, you can keep your CV skills sharp by continually reading up on the subject. You can also work on side projects in CV and you can try branching out into other areas of AI to broaden the scope of projects you are qualified for. Don’t give up on your quest because CV is a field that is going to grow – it’s only a matter of time before the industry catches on to the amazing things CV can do with their video data.

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