(asking)How do I pick a specific field within CS ?

HPE NDPm61
Oct 4 22 Comments

Background: Still in college graduating May 2020(B.S. - CS)/Intern at HPE. I have an interest in AI/ML(what a surprise), thinking of taking an offer for Data Engineer role(different company) and getting a Master's in AI/ML at the same time.
Data Eng/Master->MLE(general Idea).

FullStack seems pretty interesting too, but just like ML/AI I don't really have hand-on experience with it so I don't know truly.

Got an offer(c1) for either (Data Eng or front/full/back end Eng), just trying to decide. Thanks for the input.

Other Interests includes: Distributed Systems/OS/Parallel Computing/Cryptography
Wondering on how to go about picking a specific field or career path i.e.

Backend Engineer
Frontend Engineer
FullStack Engineer
Mobile Engineer
Data Engineer
ML Engineer
...

Fields of ML I'm interested in

Neural Networks – e.g. time series prediction
Evolutionary Computation – e.g. genetic algorithms, genetic programming
Vision – e.g. object recognition, image understanding
Robotics – e.g. intelligent control, autonomous exploration
Expert Systems – e.g. decision support systems, teaching systems
Speech Processing– e.g. speech recognition and production
Natural Language Processing – e.g. machine translation
Planning – e.g. scheduling, game playing

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TOP 22 Comments
  • So do you want us to choose your career path? I recommend unemployed
    Oct 4 3
    • HPE NDPm61
      OP
      Not a bad idea, don't have to work then...
      Oct 4
    • Grab ncvY76
      Nor eat?
      Oct 4
    • HPE NDPm61
      OP
      Big Brain, solving 2 problems at once
      Oct 4
  • New / Eng lc_for_tc
    Backend.

    At faang and other top companies you’ll prob get exposed to a bit of ml/ai stuff as a new grad/junior.

    But if you want to be a full time ml software engineer, you’ll need masters or PhD. Highly competitive roles rn.

    Backend experience at a top company will help stand out, specially if you do masters in ml/ai or PhD after.

    You can also get ml/ai swe positions with only backend experience, no masters/PhD. This is all dependant on your skills and performance.

    Please correct me if I’m wrong.
    Oct 4 3
    • HPE NDPm61
      OP
      So focus in on Backend Engineer/Get Master in AI/ML -> move into ML/AI SWE or go backend Eng -> AL/ML SWE. Never really knew Backend exp was a stand-out thing, thank you for your reply.
      Oct 4
    • New / Eng lc_for_tc
      Backend at any company (pref top company ofc) -> ai/ml swe at top company.

      If you can’t get ai/ml at top company then do masters/PhD.

      Doing ai/ml at a non-growth startup or small company won’t help in the long term without a masters or PhD.

      And yes backend swe is the most competitive out of all these (besides ai/ml swe). If you can become a backend swe, it opens a lot of doors and these other roles will be much easier to get down the road with the exception of maybe front end.

      You can do data engineer too, but IMO Backend swe is much better and more sought after (don’t get bought by the data science, big data hype)
      Oct 4
    • HPE NDPm61
      OP
      Yeah, trying not to buy into the hype. Backend > Fullstack> Frontend(lol) Seems to be the ranking. Only really considering Data Engineer due to the fact of similar technologies and Frameworks they use. Thank you for input again
      Oct 4
  • Microsoft / Consultant micrusade1
    STFU already with ML. I am bored, I see ML in everyone's Resume and when asked about basic CS questions, they are not able to answer anything. Like wtf, total turn off.
    Oct 4 3
    • HPE NDPm61
      OP
      Understandable.
      Oct 4
    • HPE NDPm61
      OP
      If we drop ML Engineer , what would you recommend
      Oct 4
    • Microsoft / Consultant micrusade1
      Full stack or BigData.
      Oct 4
  • Data engineer won't get you to ML engineer. They're completely different things and aren't very related. You'll have a better chance as a backend SWE.

    Source: I am ML engineer, significant other is data engineer, both FAAM
    Oct 4 2
    • HPE NDPm61
      OP
      Thanks for the input, seems like most people are saying do backend.
      Oct 4
    • Facebook 03!;9/),9
      You’ve got yourself a FAAM fam
      Oct 4
  • Spotify Atinlay3
    ”Neural Networks – e.g. brain modeling, time series prediction, classification”

    What?

    Brain modeling is not a thing. It’s like calling neurosurgery as brain surgery - which is incorrect.

    Time series prediction is not a deep learning thing, it’s a problem area.

    Calling classification as an area of neural nets is really pissing me off. Can you really say that these are areas of interest to you, if you cannot seem to phathom what they are on a high level?
    Oct 4 1
    • HPE NDPm61
      OP
      My b, sorry for my lack of knowledge. Any other input ?
      Oct 4
  • IEEE / IT Alov
    I don't know much about this field, but I'll suggest you go with a Data Engineer position as plan A, and a Full Stack Engineer as plan B. You actually know your stuff, concrete information, and maybe too much information that you're having a hard time deciding. Wish you good luck, sis!
    Oct 4 1
    • HPE NDPm61
      OP
      Thanks, I probably am getting pulled down by having too much information
      Oct 4
  • Google Woolf
    Based on your list, I presume you are primarily interested in engineering roles. Working on a core infrastructure team will be the strongest asset in terms of technical experience for nearly any backend eng.

    ML is far more academic in comparison, and a top practitioner should know the theoretical underpinnings down cold. One does not become a good MLE by merely calling APIs through haphazard keyword-matching.
    Oct 4 1
    • HPE NDPm61
      OP
      Thanks for the input, will prob go with Backend Role, really want to learn mainly.
      Oct 4
  • Salesforce newgrad01
    Doing only MLE can be very limiting and boring.
    Go for backend, you will have lots of exciting stuff to learn.
    ML is currently being hyped way too much. Don't fall for it.
    Oct 7 0

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