Hello blind fam, I've spent my career in the data and ML space for the past 6 years. Started at Cap 1 and then went to a series B startup (acquired), then began my own start up (failed), then joined another series B (current role). I've good experience building ML products end to end (idea, pipeline, modeling, deploy to prod) along with some good backend engineering experience. As I consider moving to a big tech company, my thought is to try to go to applied ML. I'm not a phD and am likely not qualified to do ML research (though I do have a masters in ML). And "data science" at these big companies usually does not mean the ML work I want to be doing. MLE, or applied ML is the sweet spot, from what I've gathered. (At smaller companies it's always just Data Scientist - ML as a one size fit all) My questions are: 1) how do I get interviewed? The few applications I've submitted a few months back tend to get ignored (even with referral). My assumption is it's because I don't have big tech on the resume. Is this likely true? Or does my resume just not communicate my skill well? Or am I targeting the wrong level? (More below) 2) what level should I target? With 6 YoE I was thinking an E4 and equivalent would be right. Am I crazy? 3) have I missed the boat to break in? I would really appreciate everyone's input and am open to all feedback. Also, I realize that things are not ideal now with layoffs happening in many places. But I'm living now, so am trying to do what is possible now (while continuing to be grateful for the job I'm at) TC: 180k YoE: 6
Let’s say you get the job. The issue is keeping up with the changes in this field, can you ever manager a PhD? What’s the career path? With normal tech you can rise up the ladder well. Honestly, I don’t like regular tech. And if you’re like me I get it. Got for the ML stuff. I think the best way to get a job is to apply to ML infra roles where it’s a very friendly environment. Example: at DoorDash, Spotify, Uber. I think even Amazon, ML engineers work closely with infra or applies scientist folks. It’s a lotta bloody luck too. You need to talk to the manager, an engineer on the team and see if you can join as an engineer but become an ML engineer if you want to. Etc. Even though I’m in ML I’ve had tough luck finding a good team but my resume helps me get interviews so I’ll be good. With this market people have more choice so they’ll prefer folks with experience. So just try your best I guess.
Not really interested in a PhD, hence not aiming for ML research. But staying up to date and applying ML to real world is what ive been doing and am good at. Targeting infra is an interesting strat though
Yes target MLE over DS at least at Meta and Goog. At Amzn you might like applied scientist if you are good at modeling. At Atlassian data scientist is more applied work as well. It's really annoying and non standardized terminology unfortunately. I don't have much inside knowledge, but my suspicion is that most places are targeting seniors (e5+) if anything, and that could be tough at 6 years non FAANG experience. Most companies will try to downlevel from nonFAANG. You haven't missed the boat though. It can be hard to get a foot in the door. It just depends on timing, so keep networking and trying.
Thanks, I really appreciate that. My sense is also that YoE will be discounted since it's not at faang. Do you think e4 is the right spot to target (even though openings are scant right now?)
Yes you're definitely above E3, and if I were you I would still shoot for E5 in addition to E4 anyway and just see where you can get through. Hopefully when you talk to recruiters, you can feel out the situation to see whether you can qualify for a higher level.
lie and apply bruv
Is that the only hope? No way if playing it straight?
who's gonna know? If u do good in the world with the opportunity, even god will approve