Hi, this is my friend's account. Couldn't make an account to post with my college id.
I'm interviewing for entry level Machine Learning Engineer (MLE) in near future at Adobe(Bay Area). And I can not find any resources on how to prepare for ML rounds.
What shall I prepare other than my resume projects. I have significant research and projects in deep learning and deep reinforcement learning. Following are the questions:
1. Is statistics important for me to prepare?
2. How important are classical ML methods to prepare?
3. Shall I go into mathematics of classical ML algos to remember all equations or just revising concepts is enough?
4. Shall I prepare distributed systems?
5. Shall I prepare "security and privacy in ML"?
6. Is there an ML system design round?
7. Is there a software engineering system design round?
8. Is there an ML case study round?
9. Any special tips to prepare for Adobe's behavioural round?
10. Any other helpful tips?
11. If I clear the rounds, what's the expected compensation?
I am confident of clearing coding round as I've solved 250+ LC (150 mediums, 10 hards and rest easy). But there's too much to revise for ML.
Any pointers would be helpful.
#swe #mle #machinelearningengineer #machinelearning #adobe #adobecareers #adobeinterview #interview #datascience #data
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I understand your anxiety about not getting an interview, I've been in your place a lot times, please dm me, i'll reply to it once I'm done with process.