How To Become a Machine Learning Engineer (Director of Engineering, Meta)

In today’s episode, we have Ritendra Datta, Director of Engineering at Meta. Ritendra built his career on applied machine learning back when machine learning wasn’t as popular as it is right now. He realized that machine learning will be huge because of the volume of data produced year over year was growing tremendously. 

He worked at Google for 10 years focusing on understanding search queries and built a team of 30 people and eventually move to Meta to work on Reels & video recommendations.

Timestamps:

00:00 intro

01:11 What is applied machine learning and its career path for software engineers.

04:14 What courses and skills students should focus on for a career in machine learning.

07:39 Career path and advice he would give to someone interested in transitioning into machine learning engineering.

11:25 Ritendra's experience and belief in learning by doing and discusses some books and resources that helped him in his career growth.

14:42 Ritendra discusses his learning process of managing large teams and scaling his skill set.

19:26 How Ritendra develops self-awareness and recognizes when his focus or skillset needs to change as the organization scales.

24:03 Ritendra talks about his experience of faster launches at Meta compared to Google and the pros and cons of the speed.

27:46 Ritendra's experience with burnout and how he mitigates it.

32:27 His advice on whether bringing in more complexity into projects is helpful for promotion.

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