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Comment by another_twist

7 hours ago

Me: ~10 years so not as senior but senior still.

When you are senior you know that reality is messy. Things break, networks fail, people push bugs and we are supposed to know how to get on with the chaos and keep pushing forward since solving the business problem is more important than anything else. I'd argue that you take a similar view to people management, its also a part of engineering just not the one you like. But its important if it helps solve the business problem. The other view would be managing folks is part of your career, so do your job.

Also I question that you've never seen anything new in the past 5-10 years (not being rude here, I understand that someone with 20years experience has seen plenty already but definitely not everything). For example, how much do you know about deep learning ? Are you on track with the latest trends in our inudstry ? Can you make a list of best practices to follow when building AI systems ? Maybe try looking into new areas for growth. It will be uncomfortable but worth it I think.

Please dont go into gaming. Dont do it to yourself and your family.

Experienced dev here who took a machine learning class and found it interesting. Could I get a position in it now? Would anyone hire a grey-haired ML junior? So far my experience says no, but may be bad luck so far.

  • “It depends”: what’s your prior experience, what kind of roles interest you, how big is the gap between what you have + a little ML knowledge/side projects?

    I’d argue there’s a big need for people with solid fundamental CS, sysadmin, infra skills who can bridge the gap into ML practitioner/researcher understanding. Applications or inference generally are probably easiest to break into, especially if you already have service knowledge. If you want to work on distributed training or kernel/model optimization, you probably need to prove your chops there.

    Neoclouds, startups in the AI space, maybe hw vendors are probably good places to look.