Preparing for Meta E4 (MLE)
Hi, I hope to join at meta as a MLE for ads rankings team (E4)? now, I am a recent Phd grad, I have worked with efficient ML algorithms for my Phd and mostly used Pytorch for work (but no experience with ads). Now, what other technical things (frameworks/tools/whatever you think it'll be useful) can I learn to better equip myself for success?
As a grad student, I was mostly focused on a small project at a time, so I don’t really have large scale design/distributed systems experience. Please share resources (code/just knowledge-wise, any books/papers or links etc?) that you think as an incoming MLE, I should know. Thanks a ton.
![Senior Software Engineer [E5] at Meta company logo](/_next/image/?url=https%3A%2F%2Ffirebasestorage.googleapis.com%2Fv0%2Fb%2Ftech-career-growth.appspot.com%2Fo%2Fcompany_logos%252Fmeta.jpeg%3Falt%3Dmedia%26token%3Da7a5bcc0-e178-4b5b-b71e-09bf6c6aefae&w=48&q=75){kind=small}
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Discussion
(3 comments)- 0
4 months agoTech Lead @ Robinhood, Meta, Course HeroUnfortunately, I don't know what the MLE-specific parts of the loop are like. Regardless, here's a bunch of resources:
- To understand the overall Meta loop: "How does the Meta interview work?"
- To pass the behavioral round (fairly relevant at E4): [Course] Master The Behavioral Interview As A Software Engineer
- To understand Meta culture (to help you pass behavioral as culture fit): "Is sprint planning and agile not a thing at Meta?"
- General thread on passing MLE interviews: "[Discussion] Machine Learning Interview tips"
- To pass DSA: [Masterclass] How To Ace Your Big Tech Interview - Data Structures And Algorithms
- 0
4 months agoML Engineer [E4] [OP]UnemployedHi, I think I couldn’t convey my question properly. I already passed the loop, I want some ideas about what type of knowledge/things I can study to best equip myself for an ads ML team from now till my joining (please see the 2nd para of my que). Thanks
- 14 months agoTech Lead @ Robinhood, Meta, Course Hero
Ah okay, "hope to join" made me think you hadn't passed the interview yet. The resource on understanding Meta culture should still be very useful.
I assume this other thread is from you, and I would mostly just recommend the resources there: "Onboarding @Meta E4 (MLE)"
For large-scale system design, distributed systems, etc, I recommend these:
- Taro Book Club: Designing Data Intensive Applications
- [Course] System Design Masterclass: Shipping Real Features To Production - This course is dated (I need to remake the entire thing), but you can definitely use the underlying doc as a template to scope out major tasks/projects at Meta
