AI

Why You Should Become a Machine Learning Engineer

Do you know what you want to be when you grow up? I tried a variety of things before finding my dream job as a machine learning engineer.

Do you know what you want to be when you grow up? I tried a variety of things before finding my dream job as a machine learning engineer.


As a child, I had no idea what I wanted to be when I grew up. I changed my major 7 times in college. I also worked as a data scientist, quantitative analyst, and a data engineer before becoming a machine learning engineer.


Here are a few reasons why I love it:


  1. Open Questions 


The answers to many questions can be found on Google. In machine learning, there are a multitude of unsolved problems. If you solve the problem, then you may be the first to do so. 


  1. Interesting Applications


Machine learning is applicable to many industries, including finance, tech, healthcare and more. If you have a passion, then you can specialize in that domain. If you don’t have one yet, then you can explore and move between industries.


  1. Multidisciplinary Skills


As a machine learning engineer, you use a variety of skill sets, including coding, system design, communication, math, statistics. It’s never boring.


  1. Academic Workstyle


You feel like an academic without the perils of the ivory tower. The path to becoming a PhD student or professor is full of poverty and politics. As a machine learning engineer in industry, you get paid to learn and build solutions.


  1. Impact


You have the opportunity to make and/or save companies significant amounts of money as an individual, which is compounded by your team.



  1. Community


The artificial intelligence community is still small and close knit. We like talking to and learning from each other in person and online. If you like hanging out with other machine learning engineers, then you’ll enjoy working with them too. Machine learning practitioners gather at meetups, hackathons, and conferences, which gives us an excuse to travel.


  1. Career Options


Artificial intelligence is a growing field, and your career options will grow with it. Imagine 10-20 years from now, you’ll be one of the most experienced engineers in this field. After a few promotions, you’ll have the option to be a tech lead or engineering manager. You can also move laterally to become a data scientist, data engineer, or ML-specific product manager. You have the option to be fully remote if you want to work from home or travel or be a freelancer. There’s nothing stopping you from becoming a CTO or CEO one day either!


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Questions or comments? Tweet at me. 


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