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How do you break into a career in machine learning? (2020)

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Re: How do you break into a career in machine learning? (2020)

#41

Post by pvarangot »

Mougatine wrote: post #13
morelandjs wrote: post #9

If you are in undergrad, I'd recommend something like, Math or math-heavy science BS -> undergrad research -> computationally heavy PhD -> entry level DS or ML engineer job -> senior ML job (within a year or two) If you are older and looking to pivot, I'd recommend, Data engineer -> senior data engineer -> entry level DS -> senior DS

You don't need a PhD for DS/ML Engineer. Even at FAANG, even in their research labs. Usually a PhD is only in the requirements for Research Scientist (RS). That said, I did a PhD (and am now a RS). It's a fantastic opportunity to learn fully focused during a few years. But if your sole objective is the career (which is ok!), don't do a PhD. There are much easier ways to break into ML industry.

I got a unicorn senior RS offer without a PhD from a company that had mostly former FAANG top brass after interviewing without knowing it was for RS, I thought it was DS/ML. I declined because of "culture fit". Everyone has a PhD, they assumed I had one, I don't even have a bachelors. We still hang out and laugh about it.

I had been working in Attitude Determination and Control and Optical Systems Engineering for seven years before that interview and I just like, knew the stuff from the job. I've been back on pure-SWE roles for four years already and I don't think I could do it now. I have the intuition but I couldn't white board proofs for tree based algos and manipulate integrals like I did on that interview for sure.

Re: How do you break into a career in machine learning? (2020)

#42

Post by gundamdoubleO »

jstx1 wrote: post #18
lhnz wrote: post #17

Earlier quoted context omitted.

Into what?

I want to do backend development next, I find it much more interesting (and more rewarding to work on based on the things I've done).

I ended up doing the same thing and moved to backend development at the beginning of the year. ML engineering always seemed very mystical to me but after doing it for almost 2 years I got burnt out very quickly. Partly due to some incorrect expectations I had from the role, and partly due to the work I was given either being not very interesting or very difficult to measure (in my opinion and experience at one company, of course). Backend devlopment felt much more rewarding with more concrete goals and strategies which I heavily preferred (not saying all ML engineering task are shooting in the dark, but this was very much my experience where I worked).

Re: How do you break into a career in machine learning? (2020)

#43

Post by bazmattaz »

NHQ wrote: post #24
angarg12 wrote: post #15

I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…

Are these academic types great engineers? Do you find that the academics have a major edge in domain knowledge over self taught programmer?

I lead a Ml Product team and in my experience no they’re not. The academic types are very proficient at research and exploratory data analysis. They’ll whip up a Jupyter in no time but they struggle understanding a live production system.

This is where an ML engineer comes into play, they’re not so academic but way better at writing production code

Re: How do you break into a career in machine learning? (2020)

#44

Post by spicymaki »

n4bz0r wrote: post #22
angarg12 wrote: post #15

I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…

> become and excellent engineer Is there a reliable definition to that? A good balance between technical and communication skills or something among the lines?

> Is there a reliable definition to that? Not really, much of it depends on the group culture.

However in general this should be enough: Demonstrate you can do the work by "being smart and getting things done" and by not being a sociopath. If you are an asset and not a liability, you will become an excellent engineer.

Re: How do you break into a career in machine learning? (2020)

#45

Post by bazmattaz »

drowning_sushi wrote: post #35
jxm262 wrote: post #27

Earlier quoted context omitted.

This is literally opposite of me. Would you mind elaborating a bit on the negatives of working on the ML side of things? Definitely not saying your wrong or that it's better than backend dev (it's probably just personal preference). But as someone considering it, I'd like to hear the good and bad of each type of role.

I too moved away from ML after actively pursuing it for many years. YMMV but here are my reasons - Scientists dont always make the best 'clients'. The requirements you spend months implementing may be completely obsolete by the time you are done and then completely unused. - You often dont understand or are made aware of the impact of your work. - Its challenging to compete with Masters/Phd graduates who have spent y…

Out of interest who led the team? Did you have a product manager? Ideally they should make everyone aware of the value of the work

Re: How do you break into a career in machine learning? (2020)

#46

Post by serjester »

Personally I’m moving out of the field into general software development. As a data scientist I never found myself getting into a “flow state”.

Most importantly I’ve found the impact of machine learning to be limited outside of massive companies which come with their own headaches. To add to that the number of jobs is limited and the competition is fierce.

Not to say any of this is a negative, I just recommend people only get into it if they genuinely find working on ML problems exiting enough to do in your free time.

If anyone has done something similar, I’d love to hear about it. Most recruiters seem to be pretty surprised I’d want to do this.

Re: How do you break into a career in machine learning? (2020)

#47

Post by Melting_Harps »

angarg12 wrote: post #15

I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…

> Now I interview tons of people for MLE roles.

I come from fintech, what suggestions do you give to a former dev re-entering tech via AI and ML and wants to focus on the Product Dev side of things?

I managed/collaborated with a team of 3-4 devs as a co-founder during it's peak and then did a dev and consultant stint at a mega corp after getting fed up with how bad PM can ruin everything and self-sabotaging itself.

I'm now studying a BSc in AI and ML to get back into tech and I've realized that my strengths won't be as a developer and would I'd prefer to focus on being a much better PM than what I had.

Re: How do you break into a career in machine learning? (2020)

#48

Post by NHQ »

NHQ wrote: post #24
angarg12 wrote: post #15

I moved to a Machine Learning Engineer role a few years back. I just did an internal transfer to a ML team with no previous knowledge. The team trusted me to pick up whatever I needed on the job. Now I interview tons of people for MLE roles. Trying to get in "through the front door" is incredibly competitive. Not only you have to prove you are a great engineer, but also good ML knowledge. You'd be competing with peop…

Are these academic types great engineers? Do you find that the academics have a major edge in domain knowledge over self taught programmer?

Spicy comment >_>

Re: How do you break into a career in machine learning? (2020)

#49

Post by NHQ »

angarg12 wrote: post #32
NHQ wrote: post #24

Earlier quoted context omitted.

Are these academic types great engineers? Do you find that the academics have a major edge in domain knowledge over self taught programmer?

Usually you can tell people who are purely academic. They excel at domain knowledge but are almost naive about building real world systems. They might come in as juniors. I don't think we would loop anyone as mid level or above unless they have experience delivering working systems in production. Personally I don't mind the candidate's background so far as they can do the job (how the interview is a sucky way to dete…

At the end of the day, it is about engineering. I'm self taught as a programmer, and I have also translated the latest deep learning paperwork into live code, AND i have novel research and experiments in code repos (not papers).

The thing lacking is a hacker's credibility as an ML researcher, which i think is ironically preposterous given the self-teaching of complex domains with engineered proof.

I don't see what an PhD has on the class of self taught hackers is what I'm trying to say. Just kidding, I know the answer is that they are trained in a certain institutional mentality. Give me my downvotes.

Re: How do you break into a career in machine learning? (2020)

#50

Post by lonesword »

I think most of the comments assume that machine learning engineering equals machine learning. This is always not true. If you are an MLE, chances are that you work on the infrastructure and data pipeline side of things rather than on the research. If you are lucky, you get to productionize a prototype, which might involve re-writing it, or you might get to build an in-house hugging face. You absolutely do not require a phd to do this.

Then there are these other roles which involve prototyping new ways to train a model, or taking a paper from 5 months ago and see if it works for your use case. Or you know, just work on something that you can eventually publish. At FAANG, these are usually the "Research Scientist" or "Applied Scientist" roles. Most of these require a phd, but it's completely possible to get an offer with just a masters (I did), and I know of at least one case where the person "only" had a bachelors (and some experience). But by far the most straight-forward way to break into these roles is to have a phd.

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