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: 🥜
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.
That's interesting....can you please give some examples of ml infra (is it prediction serving, etc)?
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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.
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May I please ask if there’s any good books or resources to learn more about (3)? I’m a full stack engineer and interested in becoming a MLE. Thanks!
I made the quiz based on FAAG interview exp here: https://github.com/khangich/machine-learning-interview
This is excellent! Thanks!
ISLR also covers most of the topics under your "ML Fundamentals". Really great book and preparation resource imo.
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.
I like this resource that deals with large scale ML systems: www.machinelearningatscale.com
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If you're on the job hunt and eyeing ML roles at TikTok, drop me a DM. There's no need to send me any resume, but if you've faced rejections and would like feedback on your resume, I'm here to help with that too. Just upload your resume on Google Drive and share the link. #severance #layoff #hiring #resume #ml
Can I send over my resume for review? I am unable to get call-back on MLE roles
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