Stylighters are awesome and we want to let the world know! That’s why we decided to show you what our work-life balance looks like; what we have for breakfast, what our idea of success is, and much more! Meet Marco, our Machine Learning Engineer. Who knows, he may be your future colleague!
Can you define yourself using just one hashtag?
That’s pretty reductive… but let’s go for a pun #LearningMachine
What would you say is your definition of success?
Feeling content with who and how I am.
What would you describe as your power outfit?
A guitar hanging from my shoulder. Probably some clothes too.
Biggest surprise since working for Stylight?
A positive one: feeling appreciated for what I do.
The last thought you had before going to sleep last night?
How can I feel so warm and still have cold feet.
Can you give us a word that describes your job for each letter of your name?
Model
Accuracy
Reason
Code
Optimise
Who’s the person you’d most like to have a coffee with?
Since it’s a coffee chat, let’s make it about coffee: a coffee producer who loves his/ her job. Interesting chat and great coffee guaranteed 🙂
What’s the best gift you’ve ever been given?
Probably my girlfriend flying to London to make a surprise appearance at a gig.
‘Home’ means…?
Not much. It would mean the place where I can be with my best friends, but we’re all scattered around the world.
A DAY IN THE LIFE OF MARCO:
8:00 AM:
Who am I, where am I? It will take a bit to answer these basic questions, and another hour to really wake up, so I take my time to have breakfast, make pointless conversations about last night’s dreams.
morning coffee!
9:15ish AM:
I walk to the office and pick up where I left off the day before, looking at yesterday’s work with a fresh mind.
9:45 AM:
Stand-up. My team and I briefly touch base to discuss what we have been up to the last day and the plans for today. Lots of acronyms and obscure technical lingo flying around.
10:00 AM:
Let’s roll! Some days ago I had a hunch for improving the quality of the machine learning models used for product tagging, so I dive deep again in the process of transforming an idea into a prototype that I can test. The first quick and dirty script seems to work and gives a boost of optimism, let’s build a large-scale experiment.
Noon:
Donnerstag ist Dönerstag. Silly as it sounds, eating a giant kebab on Thursday is a team tradition fulfilled with religious devotion, mostly by male engineer specimens.
1:30 PM:
My team operates in an agile framework, so be it for planning ahead or looking behind, we have a few of these meetings scattered around the week to work together the best way we can.
this is 110% what a machine learning engineer does all day
2.30 PM:
More thinking and coding: I am in the process of rewriting a large chunk of the current machine learning framework, so I will spend the rest of the day working on writing code from scratch, adapting old parts and creating tests for all of it.
6:00 PM:
Music. It does not happen often enough, but tonight I am rehearsing in the office basement with a colleague of mine who happens to be a damn good singer too. Guitar, voice, being totally unprepared: that’s a good recipe for having a good time.
7:30 PM:
The lunch döner will keep me going for a couple more hours, so I have all the time to go swimming. The public swimming pools in Munich are amazing, and it seems that each one of them appeals to a different type of person. Olympia is the best if you actually want to do some sport, and I can cycle there in 10 minutes from the office.
9:30 PM:
Finally home, tired and hungry. My girlfriend comes back at around the same time, she was at a German class. Two hungry people this late in the evening need a quick solution, so we opt for pasta with porcini mushrooms we picked up last summer. Add a glass of prosecco, and it doesn’t really get much better than that 🙂
dinner – the photo is blurry because I was so hungry 😉
11:30 PM:
Time to go to sleep after spending an hour on YouTube between snippets of documentaries by David Attenborough, gems of jazz-fusion music and comedy.
