
Ask HN: Moving into ML as a DevOps/Security Guy - _alxk
I&#x27;m looking to move into ML. Some facts about me:<p>* My background is in Security (i.e. pentesting&#x2F;red teaming, security engineering) and I spent some time as a &quot;DevOps&quot; guy. I&#x27;m comfortable with designing and building cloud environments, worked a lot on Kubernetes, poked around Kafka. I&#x27;ve reviewed security for event driven architectures etc. So I&#x27;ve seen a few things around the block and I know how things fit together in modern environments. I&#x27;m Senior in my security role.<p>* I can &quot;code&quot; but I&#x27;m no &quot;software engineer&quot;. I can throw together whatever several hundred lines of Python I need to get anything done, I&#x27;ve built quite a few frontend and backend services for side projects over the years, worked with MQs etc. but I&#x27;m no software architect. If I wanted to get hired as a software engineer I&#x27;d probably be looking at junior-mid-level positions, but I feel I would ramp up quite fast given transferable skills I have from Security and &quot;DevOps&quot;. Probably what I&#x27;m lacking most is theoretical CS stuff that would come up in interviews.<p>* I&#x27;m doing the MITx &quot;Statistics and Data Science MicorMasters&quot; part-time.<p>* I have enough savings to quit my job and spend a solid year (or even two) re-skilling without emptying the bank account.<p>* I&#x27;m not under the illusion that I can transfer to ML after a puny MicroMasters and start doing some hardcore theoretical stuff. That&#x27;s not the objective. I do seriously want to wrap my head around the work of others though.<p>What is your advice to someone in my position who wants to work on the exciting &quot;new world&quot; stuff driven by our progress with ML?<p>If you work somewhere doing awesome things with ML, where do you think a guy with my background would provide good value, with some reskilling?
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s1t5
Something to keep in mind - experienced devops and security experts are
extremely valuable, at the same time ML beginners are in oversupply. Do you
really want to put yourself at a massive disadvantage in the near to medium
term, especially if the future of ML is kind of uncertain while with your
other skillset you can have a pretty stable career?

As someone working in ML (a couple of years of experience), I'd much rather be
in your position than mine.

~~~
Aperocky
There's a huge oversupply everywhere until expert ML levels.

Just about everybody was able to tweak some parameter in models, some can
explain themselves, others can't, the end result doesn't differ that much.

The way I see it, there's 2 ways you can walk around this. By being a software
engineer that deals with the underlying ingestion/infra (that's increasingly a
solved problem too), or be the guy that actually write the ML package
themselves. Only the latter will be anywhere near secure, but that's almost 0
percent of the current supply.

I'm glad I got out of machine learning/data engineer role for a pure software
engineer.

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ystad
First, kudos for Having a growth mindset.

Some thoughts Taken with grain of salt

\- before quitting try to figure a few positions that you want to head to
after your masters and study. Is it ML scientist, Data scientist, ML engineer,
Data engineer, PhD in ml etc., use that to figure out your plan. This will
help if you want to add more time to learn algorithms and programming too.

\- what are your strategies to get a Ml job Or higher studies once masters is
complete

\- tradeoffs — a part time masters gives you the flexibility to see if you
truly enjoy, switching to fulltime has the advantage of compressing time to
speed up your learning

\- if you can intern in a ml position while doing masters nothing like it.
Network as much as possible, on campus,instructors, alumni etc

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Jugurtha
Hi. Hit me up and I'll set you up so you could have an environment that
already has pretty much all the libraries installed, where you can track
experiments, deploy and invoke models, schedule long running notebooks,
collaborate in near real-time on notebooks, have multiple check-points, and
automatically parametrize notebooks so you run experiments filling up a form.

It's a play version of our internal tool to which we invited around thirty
students of one of our colleagues for their ML projects.

This way you can concentrate on the actual courses instead of the nightmare of
setting things up and the usual ML specific problems. This should speed up
your progress, because people lose an ungodly amount of time on these issues.
Well, maybe not on course projects, but in real projects they do. I'll also
add you to the Slack workspace in case you encounter issues.

~~~
s1t5
Are you really offering an easy setup to the senior devops person? I'm sure
they can figure things out.

~~~
Jugurtha
> _Are you really offering an easy setup to the senior devops person? I 'm
> sure they can figure things out._

I'm sure a mechanic would figure out their broken car; it just is not ideal to
do so everyday on their way to their new job/course.

Plus, in this case, it is not only about mechanics (devops). The window jams
and doesn't close when it's raining. The fuel the car can fire changes every
week. The seats were salvaged from a 1920's car. Seat belts are too tight and
thin. The pedals are slippery. The sequence to turn on the car is in their
colleague's head, and he's often absent. The tyres start skidding on certain
streets. The door handle are the house door's handle and they must transfer
them back and forth every time they take the car, and the refrigerant liquid
is leaking, but there's a funnel on the dashboard the driver has put an upside
down bottle to automate filling canceling the leak.

Offering them a car that just works is in no way doubting their competence,
but merely a catalyst for the change in state they want to happen. Consider it
reducing the activation energy.

I gather from your other comment you have a couple of years of experience in
machine learning. I suppose with real deadlines and money on the line, with
colleagues working on the same project? Can you tell us more about your
workflow? How do you deliver value without dealing with jammed windows and
leaky reservoirs? Or how do you deal with that?

What's lacking? What's getting in your way? Why does the value take so long to
reach end-users?

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cik
Have you thought about getting a job in a security company that does active
software development (i.e not a pure hardware play)? Someone who wants to be
an ML head with a security background would be an asset there. I can easily
see companies like DarkTrace, and Vectra loving that type of profile, and
being interested in seeing people grow from one side to the other. It's core
to the business.

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scott31
> where do you think a guy with my background would provide good value?

Probably in devops/security stuff

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giantg2
Wow, two years worth of living expenses saved up. Kudos.

