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Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

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Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#121

Post by ptd »

bitwize wrote: post #118
ptd wrote: post #117

Earlier quoted context omitted.

Not sure if this is sarcasm, but people aren’t machines. My reply rate rose considerably by changing from my first(unique) name, to my middle(common) name. People judge, if you’re going for a new job why give them any chances to ding you?

So, should black candidates bleach their skin because "people are not machines"? Making excuses for wrongful prejudice only perpetuates the prejudice.

Depends on how badly that black candidate wants the job. I’m not making excuses for anyone, I’m just giving advice if your goal is to get the job. If your goal is to stop wrongful prejudice ignore my advice. Though one could argue the best way to stop this kind of prejudice is from the inside.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#122

Post by 773js »

daniellemswank wrote: post #5

I've hired about half a dozen ML engineers/architects in the past six months. Several of them have EE backgrounds. There's a good bit of ML that touches on hardware (think integrated cameras and similar) so it can be really helpful. You're mostly on track with your plan to build something. You do need to demonstrate that you have the skill set, but building one giant thing isn't the answer. There's so much that goes…

Your work looks interesting, would you mind if I sent you an email via the Contact Us page on your website? I'd love a chance to try to get on that call back list.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#123

Post by bra-ket »

ddoolin wrote: post #97
ryanjodonnell wrote: post #30

Earlier quoted context omitted.

Random side note, but when is the 'FAANG' acronym going to die? MSFT is killing it, prob the top tech company around these days. Needs to be included in that list.

FAANGMUA is the latest I've seen...Microsoft Uber AirBnB, I believe.

FAANGMUALCRQRASD

Linkedin, Cloudera, Redhat, Quora, Robinhood, Asana, Salesforce, Dropbox

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#124

Post by jeff76 »

agentofoblivion wrote: post #115
jeff76 wrote: post #111

Earlier quoted context omitted.

Great reply. My question based on this comment, >My advice is assuming you’d like to be a person that trains/deploys ML models to solve problems in industry. This is much different than an ML Engineer, who’s implementing algorithms in low level languages and squeezing out efficiency. Obviously that would require a much deeper understanding of SWE. And a totally different person is an academic researcher that’s develo…

I think it’s unlikely to become expert in all of those things. If you do, it’s over the course of an entire career, not to get started. I guess it comes down to how much expertise is “enough” for you. Naturally, if you split your time across 3 domains you won’t be as expert as someone who dedicated all their time to going deep in one. In the context of a big company, I think it makes sense to have a specialized workf…

This answer makes sense.

I suppose my question is more along the lines of, if someone is specializing in deep learning in a PhD program then shouldn’t they at the very least be able to implement models and also know optimization tricks?

In other words shouldn’t they be able to develop enough skills to go deep in one area but also know enough to be dangerous in the other three domains?

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#125

Post by scatter »

agentofoblivion wrote: post #98

I basically did what you’re talking about. Masters in physics, then went into semiconductors as engineer and materials scientist, then switched to Data scientist at a bank for 18 months, and now have been a research scientist in AWS for almost two years. In Amazon, it’s easy to move around, but not between job families. I think it’s a bad idea to join as a SWE and try to transfer because they want people that have do…

Great reply. Just out of curiosity, did you end up giving your semiconductor job before joining the start up with a data scientist title ?

I am deep into semiconductors, and am facing the dilemma of giving up my expertise so far, to join a startup as an entry level engineer.

I have done a couple of MOOC specializations and am trying to find projects within my industry to gain some credibility. Also trying to stay active on Kaggle to build some basic data analysis portfolio.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#126

Post by scatter »

Hi, I am in a similar boat, and would love to network with you either in person or online.

I have a PhD in EE, working in semiconductors. I have done a couple of MOOC specializations on Coursera, and am trying get some data science projects on my resume. Also trying do some Kernels / Scripts on Kaggle to build up a basic portfolio.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#127

Post by ultrasounder »

scatter wrote: post #126

Hi, I am in a similar boat, and would love to network with you either in person or online. I have a PhD in EE, working in semiconductors. I have done a couple of MOOC specializations on Coursera, and am trying get some data science projects on my resume. Also trying do some Kernels / Scripts on Kaggle to build up a basic portfolio.

Hi, Email is in my profile and I am always looking to network. Shoot me an email and we can take it from there.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#128

Post by ultrasounder »

scatter wrote: post #125
agentofoblivion wrote: post #98

I basically did what you’re talking about. Masters in physics, then went into semiconductors as engineer and materials scientist, then switched to Data scientist at a bank for 18 months, and now have been a research scientist in AWS for almost two years. In Amazon, it’s easy to move around, but not between job families. I think it’s a bad idea to join as a SWE and try to transfer because they want people that have do…

Great reply. Just out of curiosity, did you end up giving your semiconductor job before joining the start up with a data scientist title ? I am deep into semiconductors, and am facing the dilemma of giving up my expertise so far, to join a startup as an entry level engineer. I have done a couple of MOOC specializations and am trying to find projects within my industry to gain some credibility. Also trying to stay act…

Hi OP here. I don't think you need to give up Your Experience to join a startup as a Data scientist. But what won't be 100% transferrable would be your Semiconductor specific skills(think spice, process technology etc). If you have been coding your current job that is a skill that is transferrable.Your PhD is a massive foot in the door. Have you considered something like Data incubator or Insight data science fellowship which require a minimum P.hD to transition.

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#129

Post by antidesitter »

pts_ wrote: post #107
ryanjodonnell wrote: post #30

Earlier quoted context omitted.

Random side note, but when is the 'FAANG' acronym going to die? MSFT is killing it, prob the top tech company around these days. Needs to be included in that list.

How may I ask is MSFT a top tech company?

https://www.nasdaq.com/screening/companies-by-industry.aspx?...

Re: Ask HN: Engineers from non-CS background, how did you pivot into ML/AI?

#130

Post by jatins »

imh wrote: post #71

Stop focusing on MOOCs and youtube videos and study textbooks. Do exercises. Treat it like academic studying, and you'll end up with a decent education. It's important, because it's often easier to make a thing work okay than to understand why it works, so you'll get false confidence working through a tutorial. But then you want to apply that to something else and it doesn't work quite right, you won't know why it do…

My experience has been different. "Academic Studying" can be hard with a full time job, and there is often a wide gap between what you learn in books and what you do at the job.

For purely professional purposes, it's probably a better idea to take a non-academic approach.

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