Machine Learning Engineer

Election Systems & Software
tdn

Election Systems & Software

tdn
Aug 22, 2020 14 Comments

Could someone who got the job as a Machine Learning Engineer at Google, Facebook, Apple, Amazon guide me how to prepare for ML engineer roles at those companies?

Specifically, I am looking for these inputs:
1. How many LC questions should I do to feel confident and land a job in the above stated companies? Should I focus on LC medium and also hard?
2. Does Facebook/Apple/Amazon ask questions based on the list mentioned in LC with the company tag?
3. How much preparation is needed for system design?
4. Should I have deep understanding on ML algorithms including Deep neural nets?

Thanks

TC: 🥜

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TOP 14 Comments
  • IEHP
    mldesign

    IEHP

    mldesign
    I made the quiz based on FAAG interview exp here: https://github.com/khangich/machine-learning-interview
    Aug 28, 2020 2
    • BFS Capital
      Poutine

      BFS Capital

      Poutine
      This is excellent! Thanks!
      Oct 20, 2020
    • ISLR also covers most of the topics under your "ML Fundamentals". Really great book and preparation resource imo.
      Nov 14, 2020
  • Intel
    lk45kjH

    Go to company page Intel

    lk45kjH
    OP, I went through MLE loop at FB a few months ago.
    1. LC medium. Number depends on your comfort level. I had 300+ solved including FB top 100.
    2. Yes. All their questions were from tagged LC questions.
    3. Not much. For FB, understand generic recommender systems design process. Deep dive into areas like data preparation, storage, processing, ML algo, candidate generation, filtering, ranking, deployment at scale. Expect to be asked any question in this pipeline.
    4. No, according to my experience. If you have put any relevant experience in your resume you might get asked a few questions during behavioral round, but FAANG type companies mostly care about their interview bar.
    Prepare well in generic system design too since there’ll be a round for that.
    Aug 22, 2020 3
  • Google
    grossjeans

    Go to company page Google

    grossjeans
    I am not a great person to comment on the current interview prep resources since it’s after my time and I’ve never gone through it. Still, maybe some of this will be useful as perspective:

    1.no idea
    2. No idea
    3. If you are already in industry and have worked with systems at scale, there shouldn’t be anything terribly new here.
    4. Roughly, yes. It appears today that interviewers focus effectively exclusively on neural nets which I find strange 🤷🏻‍♂️ many of the underlying concepts generalize though, so having a deep understanding is extremely useful.

    All that said, my opinion is that these designations (machine learning engineer, research scientist, software engineer, etc) exist for the sake of it. The job profiles are pretty similar and depending on the team, you can get hired for many different skill sets; solid breadth, deep knowledge in a single domain, deep infra knowledge. The last one is the rarest, as best I can determine.
    Aug 22, 2020 4
    • Google
      grossjeans

      Go to company page Google

      grossjeans
      It doesn’t have to be ml infra necessarily. A lot of ml infra relies on regular infra and while most ml work at large companies is pretty cookie cutter (get data in shape quickly, understand it well, and then run all the usual suspect models over then), the key to speeding up the cycle is being able to handle the various infra components well, assuming you already understand the typical modeling challenges. Data visualizations, analysis, writing code that generalizes, are often significant blockers here. This is particularly true at a place like google where there is no obvious difference between day to day functions of eng folks.

      But there are many ml specific things too. Knowledge of target domain for the model: on device, android, compute monitoring, serving stack, user feedback stack.
      Aug 22, 2020
    • New
      aoxjdnsm

      New

      aoxjdnsm
      @Google this is very helpful, thanks much
      Aug 22, 2020
  • Xilinx
    Vada pav

    Go to company page Xilinx

    Vada pav
    this
    Aug 22, 2020 0
  • Amazon
    kitgsl

    Go to company page Amazon

    kitgsl
    MLE isn’t an official job family at Amazon at the time of my writing this. Most people on the directory are on the SDE pay scale.
    Apr 10 0