Machine Learning Career: Big Tech vs. Startup? Academia vs. Industry? Research vs. Application? - Crossminds
CrossMind.ai logo
Machine Learning Career: Big Tech vs. Startup? Academia vs. Industry? Research vs. Application?
Jan 05, 2021
|
53 views
Details
Debarghya (Deedy), currently a Founding Engineer at a Stealth Startup is a computer science graduate from Cornell University. He has previously worked and interned at Google, Facebook and Coursera. In this podcast we talk about various computer science roles in industry: research, software engineering, product management, and doing a PhD or not.00:00:07 Introduction 00:02:06 Deedy's background 00:03:00 Details about his work at Stealth startup as a founding engineer 00:04:00 Why did he shift from working at Google to a young startup? Things to know about big vs small companies 00:08:50 Factors to know before choosing between working at big & small company 00:13:15 Choosing between Ph.D and industry 00:18:10 Is Ph.D required for certain research roles as mandatory? 00:22:00 How and when did you get started with Machine Learning? 00:25:00 Difference between theoretical and practical aspects on Machine Learning, implementation vs theory 00:31:10 What did you work on at Google, Facebook and Coursera? 00:35:00 What teaches you most about ML, academia or industry? 00:38:30 Interviewing for Machine Learning roles, expectations and skill-sets required 00:46:00 How can a CS engineer apply for Product Manager (PM) roles, things to know and learn 00:56:15 Lines are blurred between an engineering manager vs product manager roles most of the times 00:57:20 What are trends in ML, in young startups vs big companies 01:04:40 General tips to any computer science student about learning and achieving goals
Comments
loading...
Reactions (0) | Note
    📝 No reactions yet
    Be the first one to share your thoughts!
loading...
Recommended