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PaperclipPerfector  9mo ago (text post)   3037 thread views

Small-Scale Question Sunday for March 3, 2024

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Seeking general high-level and low-level career advice.

Ultimate goal: Make boatloads of money, and leave the shithole country I am in (more on this later).

Background:

  • If not counting college internships, I've been working for a year. So 1 "YOE".
  • I work as a Data Scientist / Machine Learning Engineer.

My day-to-day work involves/ My strengths:

  • Writing backend code. I'm fairly decent at it (for not wanting to do it at all!), I'd say Junior/Mid-level backend engineer level. My companies codebase is a monolith built on a popular MVC framework.
  • Some frontend code. Very minimal, mostly internal tool stuff.
  • Writing complex SQL queries for analytics. Pretty fucking easy, I'm a SQL god. Also I'm the only person in my company who actually knows how to use pandas, so for the finicky analytics stuff, I'm the guy.
  • Deploying sk-learn models. Not really rocket science.
  • Prompt engineering. Company uses gpt4 to classify stuff. I have a testing set and am usually on the lookout for better prompts. Consider myself quite lucky to be able to work with LLM's in production, so early on.
  • Lots of text embeddings and vector DB stuff. Super useful for text classification tasks. I'm getting them in everywhere I can.
  • I work at a good customer facing company. Most people here know the companies name and used its product before.
  • I work 12+ hours a day and on weekends, don't see myself burning out anytime soon, I want to progress fast, and I will do what it takes.

Challenges:

  • I don't see too much position or salary growth in my current company. There isn't any ML based project I can think of that I can't do. There isn't much for me to grow into. I might be able to get a promotion or two, but that's it.
  • I think I am significantly stronger than other people in my same position with the same years of experience. I completed 7 greenfield projects by myself. All the other recent college grads and early career people I know are still twiddling their thumbs. However, I'm not a rockstar engineer who will be noticed and headhunted. I am just a good engineer. This means I won't get noticed at all without a couple of years of experience.
  • I live in Dubai, not exactly the hottest or most cutting-edge of tech markets. In other words, it's dogshit. It's genuinely fucking shit, I hate living here. I WANT OUT NOW!

My plan

  • Get more ops and infrastructure experience. The idea of writing yaml files for a living horrifies me. But I'm sure we're going to keep LLM's from deciding to turn the lights off later than we let them write our code.
  • Milk the ever-loving shit out of the fact that I work with LLM's in production. I don't make LLM's but at least I use them, must be worth something right?
  • Profit?

What would you do if you were in my spot given my ultimate goals (and shitty tech market and AI automation)? I know I can probably grind into some large MNC after 3-5 (YOE) and use that as a potential jumping-off point out of this shithole, but I want growth(or escape) NOW!

I'm not sure what boatloads of money means to you.

This probably wouldn't be enough to regularly fly out Instathots to do what thots do in Dubai, but given your SQL Godliness: entry-level/junior data scientists at FAANG-adjacent companies and more senior data scientist roles at tech and fintech start-ups/companies can make ~150K USD or the local equivalent (not necessarily all cash), give or take a few thousands to tens of thousands depending on the exact role, how they value your skillset, and your ability to negotiate. This would be more along the lines of data analytics rather than machine learning roles, which can be very different roles within a given company. There are also generally a lot more data analytics roles than machine learning roles, much less machine learning research.

Such data analytics roles typically heavily value SQL (rather than sklearn, TensorFlow, or something), thus this is where your skill-set comes in. Ultimately, it's up to you to decide as to how you weigh location, compensation, growth, personal interest, and exit opportunities, and may depend on your citizenship/residency.

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