Embarking on a new journey

Our company, the MI branch of PE, has signed a deal to be bought by company V. The news came during the Christmas shutdown of our SC facility and it was a surprise for me although most of my colleagues (myself included) sensed that the management was having some secretive M&A plan going on. We met the new leadership team from our soon-to-be-mother-company this Friday and, to be honest, I was quite impressed by the eloquence and zealousness in the new CEO’s presentation on his blueprint of the merged company. However the future company he painted, a cost leader in the MI and NDT imaging component market, was hardly the technology-focused, innovative new player as I had anticipated. He even briskly denied the possibility of us entering the system integration market. That was the time when I know that I may have to reconsider my future with the current company.

I majored in physics in college and in graduate school and I always told myself that I was lucky enough to find a position closely related to my research in graduate school. And I really was, given the situation many of my classmates are in today. It also feels good to see the awe in my peers’ eyes when I inform them my job in this part of the country where almost everyone works as a software engineer — very similar experience to what I had when I informed my better half’s colleague in the financial industry that I had studied physics for the last decade of my life. I even loved my job for many months when I was learning new things about our products on a daily basis.

Now two years into my first job out of the ivory tower, my enthusiasm in the daily routine is gradually waning and I often find myself wondering about the opportunity cost (both financial and career) of me staying at the company for the next few years. Most of the time, I spend hours implementing a simple solution I came up in seconds. The job requires more attention to detail than problem solving. I believe it is time to steer my career into a slightly different course. The foreseeable future belongs to software and artificial intelligence. Working as a physicist in a hardware company manufacturing a device based on a century old concept and a decade old technology is not quite the optimal way of spending my most creative and productive years. Not to mention the new company we are evolving into is determined to wage a price war in the ever-crowded market.

Don’t get me wrong — the past two years at the company has been rewarding. I led a team to evaluate a new type of a key product component, wrote and presented a paper; my PR has been approved; went to a different country and lead the responsibility transfer on my worn. I wish when I look back at my first two years out of college at a later stage of my life, I would recount an overall positive tale to myself and my audience. However the achievements I am most proud of seem to be accomplished out of work, the DS projects, learning Cantonese and developing a fitness habit. This may suggest that my current job is not suitable for a lifetime pursuit.

The first step of switching jobs/careers is to evaluate the core skills I have developed. I believe it is a relatively easy question since image processing that is an unchanged theme in my past positions, and I like this theme to continue in my future career.

The second step is to figure out which future field I would like to be in. This is a question with more uncertainty and one that calls for more thinking. One of the field I have been interested for years is machine learning. I know ML is not my major in graduate school and I am starting to dabble though it, but based on my philosophy of not to make any choices that I would regret later, I believe my best next job would involve some degree of machine learning.

The third step is to try to establish the missing link. Image processing + machine learning = computer vision. The answer is fair and simple, so I need to brush up on the field of computer vision.

The M&A deal will close at Q2, so I have six month or so to make myself an expert in computer vision.

  • The goal: finding a computer vision related job around the end of Q2.
  • How to get there:
  1. First, use my time at work to develop useful applications using CV that should be genuinely useful for the company as well.
  2. Second, make use of nights and weekends to read books and learn new things. Dedicate at least 3 hours a day during weekday nights and 4 hours a day during weekends. That is 3*5+4*2=23 hours a week, and 6 months would be 23*26=598 hours. 600 hours should get me somewhere in the intermediate level. At least one hour a day should be spent on summarizing the topics I have learned during the day. Keep this blog to keep track of progress and organize my new thoughts.
  3. During the first few weeks, I would expect reading several books and following along different online course to get a general feeling of the field. Make plans and adapt them to keep track of time.

Resources to start with:

  1. OpenCV crash course (http://www.pyimagesearch.com/start-here-learn-computer-vision-opencv/). The openCV book “Practical Python and OpenCV + Case Studies”(https://www.pyimagesearch.com/practical-python-opencv/) also looks good.
  2. A list of books on openCV on openCV’s website (http://opencv.org/books.html)

 

 

 

 

 

 

 

 

 

 

 

 

Embarking on a new journey