Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Ask HN: How to pivot to a Machine Learning engineer?

news.ycombinator.com

Post reply on HN
Print view View original

11–20 of 57 posts

Re: Ask HN: How to pivot to a Machine Learning engineer?

#11

Post by jampekka »

harimau777 wrote: post #5
ic_fly2 wrote: post #2

1) depends, I find ML much more interesting than software engineering. 2) Not me 3) With difficulty, but through courses like fast.ai If you’re not into maths and problem solving this is probably the wrong path. The main value add you bring is being able to transform a business problem into solvable maths. Read Introduction to statistical learning and look at the fast.ai courses. I also recommend the paper attention…

When people talk about working with ML requiring a lot of math, what do they mean? That is to say, I have a degree in electrical engineering so I learned a lot of math. However, my programming career hasn't required me to actually use it since I graduated. So I understand/"know" a lot of math. However, it would be tough for me to build back up to the point where I can, for example, solve differential equations again.…

> Does a career in ML require a strong understanding/knowledge of math or does it require you to be able to solve a lot of math?

No. With ANNs, unless you're doing research into totally new ML architectures, you're not gonna do any maths apart from some arithmetic. And even if you do, it's usually quite simple maths, mostly matrix multiplications and simple non-linear transformations of scalars.

Nothing even close to solving differential equations, and there is very little analytical solving of anything. Advanced stuff may need some statistics in the theory side, but not really in applications.

Re: Ask HN: How to pivot to a Machine Learning engineer?

#13

Post by sirfz »

I transitioned to what's now referred to as ML engineering 11 years ago, as a programmer I started working on scripts doing all sorts of ETL (in Python - was my intro to the language) and handled datasets saving and loading for training. I managed models serving (we were using Theano at the time) in prod via REST APIs. Also worked (and still do) on writing model architectures with DL experts and I can say I still don't have solid understanding of the maths but I sure know how to manipulate matrices and write ML layers/models when working with an expert.

There are other aspects to the job (like dispatching experiments) but the point is that I was able to bring value in all of this as a programmer without requiring any new skills apart from the natural learning experience that one has to go through in any discipline. I think you can surely transition as long as your job requires it.

Re: Ask HN: How to pivot to a Machine Learning engineer?

#14

Post by dailykoder »

Answer: Just do whatever the fuck is fun for you. Or has the best expected value, if you care about money.

Edit:

>i.e. can I avoid learning all the maths underneath?

Why would you want to avoid that? Math makes everything easier. Doesn't even matter which field you work in

Re: Ask HN: How to pivot to a Machine Learning engineer?

#15

Post by treprinum »

Get a PhD in ML from a top school. If you can't, get a MS CS/DS with ML emphasis from a top school, AI grad cert from Stanford at a minimum so that you can understand the latest arxiv papers. If you can't, YOLO and sift through a lot of low-quality articles on the Internet, find the gold nuggets and learn to apply them rapidly and then hope somebody will notice you and hire you. Competition is brutal right now as AI is the only area that is still hiring like crazy. I still think you are 5-10 years too late to start right now. If you can do DevOps, you can likely learn MLOps quickly but it's the same horrible job as regular DevOps. Also, data engineering is not ML but those jobs are easier to find.

EDIT: For downvoters, that's how I did it. I was a very successful SWEng (some of my work was among top posts on HN under different nicks) but saw the ball rolling towards ML in 2012 so I reskilled.

Re: Ask HN: How to pivot to a Machine Learning engineer?

#16

Post by hzay »

harimau777 wrote: post #5
ic_fly2 wrote: post #2

1) depends, I find ML much more interesting than software engineering. 2) Not me 3) With difficulty, but through courses like fast.ai If you’re not into maths and problem solving this is probably the wrong path. The main value add you bring is being able to transform a business problem into solvable maths. Read Introduction to statistical learning and look at the fast.ai courses. I also recommend the paper attention…

When people talk about working with ML requiring a lot of math, what do they mean? That is to say, I have a degree in electrical engineering so I learned a lot of math. However, my programming career hasn't required me to actually use it since I graduated. So I understand/"know" a lot of math. However, it would be tough for me to build back up to the point where I can, for example, solve differential equations again.…

Visualizing 3D matrix multiplications, and getting comfortable with it. Then there's basic calculus in understanding gradient descent. Can't think of any other advanced math that was necessary to grok the innermost workings of most models today.

Source: I won a silver medal in a kaggle competition after 6 months of ML self-learning.

Re: Ask HN: How to pivot to a Machine Learning engineer?

#17

Post by padthai »

treprinum wrote: post #15

Get a PhD in ML from a top school. If you can't, get a MS CS/DS with ML emphasis from a top school, AI grad cert from Stanford at a minimum so that you can understand the latest arxiv papers. If you can't, YOLO and sift through a lot of low-quality articles on the Internet, find the gold nuggets and learn to apply them rapidly and then hope somebody will notice you and hire you. Competition is brutal right now as AI…

He does not want to be a AI/ML researcher, but a ML engineer.

Re: Ask HN: How to pivot to a Machine Learning engineer?

#18

Post by treprinum »

padthai wrote: post #17
treprinum wrote: post #15

Get a PhD in ML from a top school. If you can't, get a MS CS/DS with ML emphasis from a top school, AI grad cert from Stanford at a minimum so that you can understand the latest arxiv papers. If you can't, YOLO and sift through a lot of low-quality articles on the Internet, find the gold nuggets and learn to apply them rapidly and then hope somebody will notice you and hire you. Competition is brutal right now as AI…

He does not want to be a AI/ML researcher, but a ML engineer.

Companies are picky. FAANG don't need puzzle solvers but want them anyway.

Re: Ask HN: How to pivot to a Machine Learning engineer?

#19

Post by LorenzoBloedow »

sirfz wrote: post #13

I transitioned to what's now referred to as ML engineering 11 years ago, as a programmer I started working on scripts doing all sorts of ETL (in Python - was my intro to the language) and handled datasets saving and loading for training. I managed models serving (we were using Theano at the time) in prod via REST APIs. Also worked (and still do) on writing model architectures with DL experts and I can say I still don…

I'm looking into learning more about ML and how I can create my own models. I enjoy math, but when I read research papers the formulas sound like gibberish. I also like the idea of Kaggle competitions, do you think I need to have research-level math understanding of ML models to do well on Kaggle?

Re: Ask HN: How to pivot to a Machine Learning engineer?

#20

Post by wcrossbow »

dailykoder wrote: post #14

Answer: Just do whatever the fuck is fun for you. Or has the best expected value, if you care about money. Edit: >i.e. can I avoid learning all the maths underneath? Why would you want to avoid that? Math makes everything easier. Doesn't even matter which field you work in

> Math makes everything easier

This can't be overstated enough. Understanding the math behind what you are doing has the capacity to turn mind boggling hard problems trivial.

Post reply on HN