Full-stack Machine Learning Engineers are becoming one of the hottest commodities out there.
Full-stack machine learning engineer is the person that’s capable of working on the design, implementation, deployment, and maintainance of a machine learning system.
Different people expand or contract the term “Full-Stack” at their convenience.
That’s ok. We don’t need a dictionary to talk about this.
Full-stack is when you can work on end-to-end systems.
That’s ok. We don’t need a dictionary to talk about this.
Full-stack is when you can work on end-to-end systems.
There’s certainly an arbitrary size of the concept “full-stack” for which the qualified population is 0.
Fortunately, is up to us to decide how much we want to tack on.
Full-stack is way smaller than “can do everything” but is larger than “purely specialized.”
Fortunately, is up to us to decide how much we want to tack on.
Full-stack is way smaller than “can do everything” but is larger than “purely specialized.”
Many don't like the term "full-stack" 'cause it evokes the thought of employers asking too much from employees.
I get it.
But the reality is that outside Big Pocket Companies that build full-blown out teams of specialists, most companies need generalists wearing many hats.
I get it.
But the reality is that outside Big Pocket Companies that build full-blown out teams of specialists, most companies need generalists wearing many hats.
Communication is key.
(Not only in MLE but for any technical role.)
(Not only in MLE but for any technical role.)
https://twitter.com/jdegourville/status/1452403636231884806?s=20
Another great way of putting it:
https://twitter.com/adipolak/status/1452232045342728201
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