
Shifting Careers to Autonomous Vehicles - dsr12
https://towardsdatascience.com/how-i-found-my-current-job-3fb22e511a1f
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lostdog
Props to the author--landing your first deep learning position is very
difficult. There are many many engineers who want to do deep learning but
don't know how, and a few employers that badly need deep learning experts. The
employers are (understandably) skittish about taking a chance on hiring
someone without expertise and assuming they can train up. If you can show up
with proof that you can train performant models, then you'll have a much
easier time. Certainly the author put in his time to build up this proof.

By-the-by, if you want to work on autonomous vehicles and aren't too attached
to being neck deep in the deep learning parts, nearly all autonomous vehicles
companies need an army of engineers for data handling, and on-vehicle
performance.

(Vladimir, if you're reading this, I'd be curious to hear what your $$$
investment was for your kaggle competitions).

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Animats
The amusing thing is that people assume autonomous vehicles are a deep
learning problem. So far, the pure deep learning people haven't done all that
well at it. Most of what Waymo does is geometry and sensor fusion. Visual
object recognition and future behavior of moving obstacles is used, too, but
that's not the core of the system. Look at their videos, showing an above view
of what's around the vehicle and "fences" showing where it shouldn't go.

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bitL
I always find it funny when I see some British recruiters' posts in my
LinkedIn network regarding "awesome Deep Learning opportunities" who require a
PhD from a top school, publications at top journals/conferences and offer 65k
GBP. Or some "super hot" Deep Learning startups seeking engineers for
$3500-5500/month before taxes. For some, having Stanford Deep Learning on
resume means one would satisfy minimal requirements for fixing bugs in their
crappy robotics system (and they are nothing like Tesla).

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duaoebg
It’s a class thing in the UK. I recommend anyone who is any good to jump on a
plane to the Bay Area. Same goes for Australia. They refuse to pay
competitively and then wonder why they can’t find good talent.

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systemtest
Here in the Netherlands they will pay competitively... for management
positions. Even middle management gets compensated very well. Engineers not so
much.

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readyoubestbook
I am also a dev in The Netherlands, while a lot of data is available for devs
in the US I can't find something similar for NL. What would you consider a
competitive pay for devs in NL? (Assuming we are talking about the Amsterdam
area for the junior, medior resp. senior levels)?

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thecleaner
I love posts like these. The author really has awesome persistence and great
sense of initiative. Its really good that Kaggle now has GPU training
otherwise AWS or GCP will just burn a big hole in your pocket. Handson
experience with this some time back.

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KKKKkkkk1
The credentialism in deep learning is absurd. This guy has a PhD in
theoretical physics from UC Davis, he's winning competitions on Kaggle, and he
can't even get an interview.

 _I remember that moment to this day. I am standing at the scene. The
organizer is preparing a check and some gifts. Alexey and I emerge
victoriously, but I can’t help but feel frustrated by the apparent absurdity.
How did this happen that some random dude that does not have domain knowledge
in medical imaging got first places in both challenges? And yet, people that
make money for a living working on medical imaging use much weaker models?

I asked the audience: “Do you know where do I work?” Noone, except one
organizer who checked my LinkedIn profile knew. I told them that I work at
TrueAccord, a debt collection agency and that I did not train deep learning
models at work. I lamented that I was not able to break away from this model
because HRs in Google Brain and Deepmind did not even look at my resume._

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6gvONxR4sf7o
I don't know where you got the idea he couldn't get an interview.

>During that same period, I had failed an onsite interview at Descartes Labs,
and a few technical screens.

>Somewhere around that time, I was invited for the onsite interview with
NVidia, which I also did not pass. One of the issues that I had was my limited
knowledge of how 2D object detectors work.

>The next company on my list was Tesla. The recruiter contacted me because of
my Kaggle achievements, which did not happen often. I passed take-home tests,
tech screenings, and an onsite interview. The next steps were the background
check and approval of my application by Elon Musk. I did not pass. [He'd
violated a pretty bullshit sounding NDA]

>The company that was organizing the competition was called Planet Labs. They
had an open DL Engineer position, I asked about it and was invited to an
onsite interview. I failed again. The feedback — not in-depth DL knowledge.

He got a number of interviews, which he didn't pass. Is it really so
surprising that Google Brain and Deepmind are going to be pickier than most?

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OnlineGladiator
I guess my question is how did he win the competition if he doesn't have
enough knowledge to pass the interview? Maybe the interviews really aren't
great at actually discerning who can create great DL models? I mean it's
possible there are other reasons as well - but the guy objectively beat a
bunch of credentialed people in an open competition.

~~~
6gvONxR4sf7o
There are a bunch of options here. Maybe they were looking for someone to do
novel research. Maybe they wanted someone who can communicate with business
partners. Maybe the competition is just people in the middle of their degrees
spending an evening on it. Maybe it is just credentialism. Maybe a zillion
other things.

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thathoo
Kudos to your effort and resilience even in the face of failures. You faced
your challenges head on and took the bull by the horns! Love it!

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2sk21
Very impressed how the author was able to bootstrap your way into a good job.

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ct0
This is inspiring! Excellent work and write up. Thanks for sharing.

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realbarack
This is an inspiring story. Nice work and well-earned!

