Machine Learning is undoubtedly one of the hottest career options in the tech-biz world today. Many aspiring youngsters are taking up machine learning jobs such as that of an ML engineer or an ML architect to become a part of the digital revolution that’s spreading like wildfire throughout the globe. But, have you ever wondered, how does an ML engineer spend an entire day?
That’s what we’re going to show you today – a day in the life of an ML engineer!
Morning – The Beginning Of A Very Busy Day
6-8 AM: Although you may be surprised to hear this, it’s true that most ML engineers take fitness very seriously and hence, their mornings usually start with some basic exercising or hitting the gym followed by a shower. After breakfast, it’s time to head straight to work.
9-10 AM: This is the hour to catch up on the projects and code that had been in operation through the night; checking work emails and checking the day’s task-list on Trello or Todoist or Google keep.
10-12AM: Work calls! It’s time to sit on the desk and get cracking with ML tools and projects. The real work begins with coding or designing a database or learning new things using resourceful tools like Scikit Learn, Spark MLlib, H2O, and the like.
Noon – A Break From Work & Back To Work Again
12 PM: It’s lunchtime! This is the time to catch up with your colleagues, discuss work and life in general while munching on food. On busy days with too much work pressure, you can see ML engineers having lunch at their desk itself while concentrating hard at work.
1 PM: The afternoon time post-lunch is usually reserved for office meetings and client calls to discuss the progress of the ongoing projects, proposed ideas for new projects and products.
2-5 PM: Completing ongoing tasks; writing unit tests, or testing the completed models. Once these are done with, it’s essential to check up on existing models, their metrics, and comparing those metrics to the model baseline. Review requests from the client’s side and do the needful. Continuing with coding.
Evening – Wrapping It All Up
6-8 PM: It’s evening now and this means that all the code requests, database models, and projects have to be wrapped up after incorporating the necessary changes. Nothing should be left hanging halfway.
8 PM: Head back home. Get some rest and maybe cook dinner. If it was a long day at work, probably ordering food from the favorite food joint.
10 PM: Checking emails one last time to see if there are any work-related issues and solving the ones that demand immediate action. Finally, ending a very productive day by dozing off for a good night’s sleep!
So, that’s basically how a Machine Learning engineer spends his day learning and building new things. Interesting, isn’t it?