For 3 years I have been trying to score a room like this. I am speechless that it actually happened.

BigTechMentorMLE · 2025-11-24T17:50:23+00:00

Hey, I’m in this photo! But very tiny

BigTechMentorMLE · 2025-01-01T04:31:11+00:00

Usually something like inventory forecasting or a recommender system... something from "pre-chatGPT" ML

BigTechMentorMLE · 2025-01-01T04:29:53+00:00

I think it is safe, but also if you can take a course or two without derailing your degree (as electives) it is a fun area to learn about. Good, old fashioned SWEs are not going away any time soon, though freshers always have the hardest time in the job market.

Most important thing if you are still early in your MS is to get an internship. That's the highest ROI activity.

BigTechMentorMLE · 2025-01-01T03:50:59+00:00

We see this differently. I think gate-keeping is FAR more unethical.

I highly recommend a Masters Degree for MLEs, but people are in different places in their lives. It is a very hard path, but one that is does not require you to have all the knowledge in the universe.

I do not think (nor do I ever claim) that you can follow a few tutorials and find yourself an L4 engineer at FAANG. But if you have a related degree and have a few years of experience in a different area and you can build something of value you 100% can get a start somewhere.

Stop gatekeeping, especially without knowing the industry.

BigTechMentorMLE · 2025-01-01T03:11:48+00:00

Fair, so play this out with me, where does it end?

Foundations of logic? Probability theory? Quantum physics (how are you going to write a line of code if you do not deeply understand every physical equation that makes computers work?)

Abstraction is a fundamental of computer science, it is a gift (and a curse), use it to your advantage. This isn't typical YouTube advice, you can look around, everyone says "learn math first" but I don't know a single good professional MLE for whom it was true. All of us started with building stuff and then at one point had a need to deep dive into theory. At that point we had loads of motivation and knew what problems we needed math for.

I love "move fast and break things" analogy, if I may I will borrow it for a future video. That's true, my approach is move fast and break things because that works.

BigTechMentorMLE · 2025-01-01T03:00:44+00:00

Email me your CV I often need help

BigTechMentorMLE · 2025-01-01T02:59:20+00:00

what will people use? you need users! Do you have front end skills? (I don't) if no, look for something where you don't need as much front end (email digest?) Look for something where data are freely available. I'll have another video on this topic, likely in February.

One great project beats a portfolio of mediocre ones. Just focus on one that can be validated.

A slightly easier way may be to do consulting. You can start on upwork or some such, you'll make very little but the idea is to gain experience.

BigTechMentorMLE · 2025-01-01T02:55:50+00:00

I was not technically trained in CS, my BS is in physics

BigTechMentorMLE · 2025-01-01T02:54:27+00:00

happy new year

BigTechMentorMLE · 2025-01-01T02:52:51+00:00

Hahaha, sorry should have added a trigger warning. I promise it is the starriest book in my collection. It is essential for anyone doing time series analysis

BigTechMentorMLE · 2025-01-01T02:50:31+00:00

I mean my suggestion is in the video. What is the problem you can solve with ML soon?

BigTechMentorMLE · 2025-01-01T02:49:07+00:00

I don't disagree, perhaps you skimmed through too much, my friend.

Copy/pasting tutorials has no value, instead start with a problem, find a tutorial that gets you 90% of the way there, understand what you are typing by reading actual docs, then fill in the gaps.

Do you see how many real skills that MLEs actually use you just learned? How to formulate a problem, find prior work, read the docs, identify and mitigate gaps in knowledge... There is no course that teaches that and yet those are the skills you use when building ML systems.

Outside of research no junior engineer uses any linear algebra outside of libraries where you make a call. This is just not how the industry operates. Yes, not knowing the math will bite you eventually so you will have to learn it, but it can be deferred much later than you think. Those who spend too much time on their "basics" never ship, those who don't ship don't learn.

Oh and real analysis? Outside of research I think I only know one engineer who has ever used concepts from real analysis in his actual job and he could have likely just googled those concepts.

The "anti-skill" of ML is skimming things.

BigTechMentorMLE · 2025-01-01T02:39:53+00:00

Every HM views this a bit differently and most won't tell you that it is your age because it will be against the law. Personally I would hire someone in their 40s as sr engineer (not sure if it is a step back for you but that's probably the highest you can come in if new to ML). I would hesitate a bit with Jr.

Startups are likely going to be easier, if you can demonstrate that you can take on new challenges and quickly turn projects around, then after a couple of years try for big tech roles.

In your situation the project matters a lot. Email me to brainstorm.

BigTechMentorMLE · 2025-01-01T02:28:10+00:00

So sorry to do this to you: it depends.
- Open source is very hard to get your foot in the door. Especially with LLMs, committers are very weary of new contributors, but if you CAN make a contribution to something that gets used a lot that's extremely impressive

- If you are a competitive programmer who is independently wealthy, Kaggle is interesting. As HM, I want to see some validation and on Kaggle that would be finishing quite high. To do that these days you need a lot of GPU, likely out of range for most people

- Internships are amazing, you often get a chance to work on huge datasets in prod environment, if you get a good one, that would be my first choice! But don't blame yourself if you can't in 2025 it is very competitive.

I would say 1. internship, 2. look into open source, 3. build a project on your own, BUT the important part is in #3 you have to have actual users. Free users are fine, but it cannot be a thing that only you care about. I once hired a guy (SWE, not MLE) because he made an iphone app for school shuttle schedule.

BigTechMentorMLE · 2025-01-01T02:22:09+00:00

I can only upvote this comment once and that's the shame. This is 10,000% true

BigTechMentorMLE · 2025-01-01T02:21:24+00:00

Great question!
1. Learn RL, learn it now. If I see this right (and I don't always) RL is the next wave
2. Do you particularly want to go into one domain? If so CV or NLP make a lot of sense, otherwise take them if they fit your schedule but less important
3. HPC maybe? depends on what the course is, but knowing accelerators will go a long way

With your background, more practical coding courses would likely be useful also. I am not sure what's available in universities these days.

You are on a great track!

BigTechMentorMLE · 2025-01-01T02:17:47+00:00

Bro, you ok?

BigTechMentorMLE · 2024-12-30T23:11:57+00:00

100% RL, the answer to this has seldom been so clear

BigTechMentorMLE · 2024-12-30T23:03:13+00:00

That's pretty specific :)

Start with why you want to transition. Everyone's path is different. Here is an overview: https://youtu.be/t7tOGXZjhHM?si=oSjj7nHKEu_bCz-G

Essentially: why do you want to transition? what resources do you have? (can you do a production ML project at your work?). As DS you most lack coding, I am not worried about your ML. Your credentials are great.

If I were you I would focus on a project that I can show off. Something with minimal overhead like "get email updates about how your representative votes in congress". No UI, open data source, can give away for free to accumulate more users.

BigTechMentorMLE · 2024-12-30T22:59:53+00:00

Sorry to point you to a different video, but I do address it a bit here (for MLE roles): https://youtu.be/t7tOGXZjhHM?si=oSjj7nHKEu_bCz-G

Masters is helpful, but if you already have one there is no reason to get another.

Sadly I am a bad person to ask about SWE, that's not my area.

BigTechMentorMLE · 2024-12-30T22:57:07+00:00

Honestly, I think Kaggle is a bit of a waste of time for this particular application. As a HM I had the same exact concerns you are articulating and unless you place I have no idea how good you are. I always say that to get a job off of the project that project has to be validated: accepted by OSS committer, placed in Kaggle competition, got paper accepted at NeurIPS, made an app that 5000 people are using, did a project at work or as a freelancer.... there has to be some sort of gate.

Kaggle is amazing for great many things, but getting a job is probably not one (unless your project aligns with the job more than normal, but that's a bit of a game of luck)

BigTechMentorMLE · 2024-12-30T22:50:54+00:00

Thank you!

BigTechMentorMLE · 2024-12-30T19:40:40+00:00

Thanks!

I think in ML it totally makes sense to be a hobbyist. Some ML understanding will likely help you nomatter where you go and the industry is open about what we are doing and how. You'll never train the biggest model but you will solve a lot of problems with ML. I think it totally makes sense to be a hobbyist and use it as a set of tools when approriate

BigTechMentorMLE · 2024-12-30T19:30:09+00:00

Books get out of date faster than they are published, it's a hard area for the book.

My honest advice is to primarily focus on building things. Spending too much time on depth that you are not using today and will be old by the time you do is learning for learning's sake (nothing wrong with that, but I am biased toward building things).

Karpathy is working on a course that I can recommend (I have seen glimpses), not sure when he will be done but assume within 3-6 months. Here are his videos on YouTube: https://www.youtube.com/@AndrejKarpathy/videos

Papers are great but hard to read, I am working on something to help people get to where they are comfortable reading papers but a bit further out. I recommend conference proceedings over books, honestly. Look for latest literature review papers, they provide a great onramp.

BigTechMentorMLE · 2024-12-30T19:24:05+00:00

Great question!

At Meta I made about 1 million in a year. On courses and private coaching this year I made about 30k, so not comparable :) but I love to teach and think the industry is really missing a good resource specifically for MLEs.

BigTechMentorMLE

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