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I've switched domains four or five times now. I started with gamedev, went to finance, then pentesting, then machine learning. The key is to have a strong port

I've switched domains four or five times now. I started with gamedev, went to finance, then pentesting, then machine learning. The key is to have a strong portfolio. Every successful switch was based on that. Even in areas where you can't really show a portfolio, like pentesting, I was good at it and was able to demonstrate it. It's really that simple. Be good, and show that you're good. Don't wait for someone to show you what to do. Oh, as for the mechanics of getting the job, it's the same as any other: Forget the resume process. Find someone in the industry you want to work at, flatter them (everyone likes to be flattered, and you should lean on this tool as much as possible) and show them you can be useful.

__dave__ 3y ago
Nice. I've worked for awhile in backend dev and infrastructure/cloudops, and thought about trying to transition to pentesting to try something new. What did you like about it? What did you not like? What made you decide to leave the domain for ML?
- sillysaurusx 3y ago
  It's mostly a writing gig. (tptacek disagrees, but that's fine -- we disagree on lots of things.) You don't really make anything, and I liked making things. It was kind of that simple. But! I also met some of the most interesting and capable people I've worked with. So if you're interested, I encourage you to give it a shot. As for "why ML," I liked ML and it was full of mystery, which was good enough for me.
  - __dave__ 3y ago
    From the outside looking in that's pretty much what I guessed: Lots of report-writing and little if any programming, but a lot of very talented and interesting people. It seems like with the proliferation of bug-bounty platforms today, there's a fairly clear way to prove yourself and get in the door while picking up a little cash on the side. Heck, maybe just dabbling in bounty programs is enough to scratch the itch.
  - maxlamb 3y ago
    For your switch to ML did you also work on a portfolio of ML projects? If so, what's an example ML project you worked on that you were able to show your future employer?
PaulHoule 3y ago
It helps to be be entering areas where demand is exploding and the supply of experienced people is thin. I have a long track record of being fast to pick up the methods of new domains and I’ve frequently had people riding my tail to help them out with a project in a new domain, even if I wasn’t really that interested in the switch. It’s a part of my origin story because the whole reason I left physics and went into software development was that I watched one of the best physicists of our time crying every night because he had no idea where his next job was coming from despite having written half of a very good textbook and numerous great papers. He made it big in the end but I had neither the tolerance for that nor the talent or motivation. I’ve had the occasional job search that took most of a year but I’ve had some that lasted 72 hours. Thus I skip all the fancy programming languages and work in the big commercial ones in demand unless I get cash on the barrelhead. For years I avoided Python but I worked for a few people who needed “data science” so they paid for my education.

__dave__ 3y ago

Nice. I've worked for awhile in backend dev and infrastructure/cloudops, and thought about trying to transition to pentesting to try something new. What did you like about it? What did you not like? What made you decide to leave the domain for ML?

sillysaurusx 3y ago
It's mostly a writing gig. (tptacek disagrees, but that's fine -- we disagree on lots of things.) You don't really make anything, and I liked making things. It was kind of that simple. But! I also met some of the most interesting and capable people I've worked with. So if you're interested, I encourage you to give it a shot. As for "why ML," I liked ML and it was full of mystery, which was good enough for me.
- __dave__ 3y ago
  From the outside looking in that's pretty much what I guessed: Lots of report-writing and little if any programming, but a lot of very talented and interesting people. It seems like with the proliferation of bug-bounty platforms today, there's a fairly clear way to prove yourself and get in the door while picking up a little cash on the side. Heck, maybe just dabbling in bounty programs is enough to scratch the itch.
- maxlamb 3y ago
  For your switch to ML did you also work on a portfolio of ML projects? If so, what's an example ML project you worked on that you were able to show your future employer?

PaulHoule 3y ago

It helps to be be entering areas where demand is exploding and the supply of experienced people is thin. I have a long track record of being fast to pick up the methods of new domains and I’ve frequently had people riding my tail to help them out with a project in a new domain, even if I wasn’t really that interested in the switch. It’s a part of my origin story because the whole reason I left physics and went into software development was that I watched one of the best physicists of our time crying every night because he had no idea where his next job was coming from despite having written half of a very good textbook and numerous great papers. He made it big in the end but I had neither the tolerance for that nor the talent or motivation. I’ve had the occasional job search that took most of a year but I’ve had some that lasted 72 hours. Thus I skip all the fancy programming languages and work in the big commercial ones in demand unless I get cash on the barrelhead. For years I avoided Python but I worked for a few people who needed “data science” so they paid for my education.