[HN Gopher] Ask HN: Has anyone made the transition from app deve...
___________________________________________________________________
Ask HN: Has anyone made the transition from app development to
ML/AI work?
I've been building Rails, Python, Node and, you name it, frontend
JS web app development for the last 12 years. I think I've gotten
too bored with the same challenges that app development presents.
Has anyone made the official career pivot to the ML/AI field? What
did you have to do? Did you have to start from a lower-level entry
into the field?
Author : sourcelabs
Score : 45 points
Date : 2023-03-13 21:40 UTC (1 hours ago)
| f6v wrote:
| Not exactly AI/ML, but I had some years of experience in Android,
| then RoR and engineering management. Then got an MS in
| Bioinformatics and now do PhD in Medicine. Which is really data
| analysis of sequencing data. I use some "AI" models as well. I'm
| doing a PhD at a company, away from the academic institution
| where I'm formally enrolled. So it's kind of like a regular job.
|
| But I've also seen colleagues pivot into data engineering.
| They've done it within the same company by simply asking, I
| guess? When there's a role available and you do your homework
| there's a chance to change the field.
| bilekas wrote:
| Could you define what you mean when you say :
|
| > Has anyone made the official career pivot to the ML/AI field?
|
| If you're talking about using ML/AI related tools and algorythms
| and taking advantage of what they can do, maybe for data
| processing etc then that's not really too hard an ask, infact
| these days depending on your role there could probably be a
| natural progression into these areas.
|
| The problem comes from the core of these types of work, so
| creating the algorithms, building new model, processing the raw
| data into something that is useful and this involves even being
| really close to the hardware level too. I find that it's hugely
| academic and mathematical focused, for obvious reasons.
|
| It's certainly stuff that flies over my head and for me
| personally no matter how interested I am in it, I don't think it
| will ever 'click' for me.
| PaulHoule wrote:
| I've gone back and forth. On the other hand, I have a Physics
| PhD.
| echelon wrote:
| Quit my job in Fintech to work on my own AI startup.
|
| I built https://FakeYou.com as a side project, and it blew up. I
| quit my job after I realized the potential, added monetization,
| and started to broaden what we do.
|
| I've been working on https://storyteller.ai for a year and plan
| to launch our platform soon.
|
| Both of these tool sets reinforce one another.
|
| I'm hiring folks that were engineers that want to do AI instead.
| Please reach out! Our stack is Rust / Unreal / Pytorch / k8s.
| haskellandchill wrote:
| you can do anything if you are able to convince your interviewer
| that hiring you will work out. I transitioned from web dev to
| data science by getting a VP of data science to work with me as
| lead engineer on their projects then studying in my free time and
| doing well on data science interviews to get a lead data
| scientist position. I went back to software engineering and now I
| am thinking about the same as you are. I will leverage my Data
| Science background, study, and do some ML projects. That should
| make me competitive in interviews and I expect to transition by
| the end of the year.
| s17n wrote:
| OpenAI has their residency program:
| https://openai.com/blog/openai-residency
| OhNoNotAgain_99 wrote:
| [dead]
| LZ_Khan wrote:
| From my experience, there are plenty of teams in FANG that will
| hire you as a backend developer in a ML team assuming you can
| pass their interviews. 90% of the work in these teams is not core
| ML and is more mundane work supporting these models, such as data
| piping, cleaning, feature generation, experimentation, and real-
| time serving. You'll get plenty of experience in working directly
| with ML systems.
|
| The jump to core ML is a bit trickier. Competing with people with
| PhD's is a drag. Wish people could also give me some tips there.
| safog wrote:
| FWIW I worked at Amazon in one of these teams and it's not
| something I found very interesting. You get thrown a random
| binary that some ML researcher compiled with instructions to
| host-it. No sense of ownership over the product, you're just an
| Ops frontend for a researcher so they can do the fun stuff
| building models and you're dealing with the pagers.
| gardenhedge wrote:
| That sounds like the worst kind of tech position to be in
| LZ_Khan wrote:
| As a sort-of counterpoint I work at a non-amazon FANG where
| I am much more involved in model training and evaluation. I
| still have never needed to define a model myself, but it's
| much more complicated and far more ownership than someone
| throwing me a binary. I think that speaks much more to
| what's going on in Amazon hah.
| [deleted]
| jamal-kumar wrote:
| As long as you're interacting with it at a decently high level
| it's honestly really easy code.
|
| I watched a friend of mine who went from maybe some python
| courses to writing some really impressive ML stuff as her first
| project within a few months and with some help from some people
| who know their stuff a bit, which I found pretty impressive. I
| think as long as you're building things on top of what's
| available out there that you can find tons of utility in all the
| solutions that have been coming up in the past years without a
| ton of effort. Try dipping your toes into something simple like
| object recognition and you'll find it's pretty easy.
|
| If you're talking about getting into the field on a level where
| you're actually developing these technologies themselves then I
| hope your math is around college-level. Reading deeper into the
| docs of the tools I'm using and they're showing calculus and
| linear algebra to me. I don't pretend to understand it very well.
| itake wrote:
| I am in the process of making this transition now.
|
| I joined Grab.com on their Safety team and started working on
| their face recognition technologies. This got my feet wet in ML.
| Now I am leading their content moderation efforts.
|
| TL;DR: Find an "ML adjacent" engineering role and take on ML/AI
| work.
|
| "ML adjacent" roles could be, content moderation, safety, ads,
| and search.
| ddlutz wrote:
| When did you join and how is it going? I had an offer from them
| ~4 years ago and this was one of the teams that I was in talks
| with.
| navbaker wrote:
| I work at a large university affiliated research center and this
| is extremely common in my department. Our software devs have to
| be at least familiar with bleeding edge ML processes and several
| just in my group of about 60 have gone on to shift to more of an
| applied research role. We have a bunch of PhDs in math and CS,
| but no one cares what degree you have if you can produce.
| smrtinsert wrote:
| How different is the compensation between typical backend eng and
| backend ml eng? Not including designing the model itself as that
| seems to be the domain of phds it seems
| oneplane wrote:
| The 'field' is rather big, and as with most tech fields, 80% of
| the work is the same (sometimes mundane) stuff. Infrastructure,
| CRUD, business logic, the whole 12-factor thing.
|
| Where it would start to get tricky is if you have to do more than
| 'consume' ML libraries. Everyone can learn how to use a library
| or API, and getting some training going isn't all that hard
| either. But if you have to build said library, or come up with a
| new modelling method, that's where it's a real transition and
| gets really hard to simply 'switch'. It's also one of those areas
| where a PhD really helps, not from a "certification-as-entrypass"
| perspective, but because this gets down to hard science. For most
| companies, however, that's a point they never reach.
___________________________________________________________________
(page generated 2023-03-13 23:01 UTC)