Before this gets inundated with people making comments about Googler data scientists making $400k, these are folks with PhDs in math or statistics, very accomplished academic literature, leaders in their fields. These are not people messing around with Haskell on the weekends and leaving an insurance firm's IT department to go to Google.
Re:Uber and Waymo Reach Settlement
by snotrockets on Friday February 09, 2018 @03:26PM
(#16343556)
They also don't make $400k – an engineer that costs $400k doesn't get that in take home pay.
There are enough non-executive engineers at Google making half a million or more base/cash comp that you could fill a room with them. That's not the point.
Entirely not true.
If self-driving car ML is "data scientists replacing a driver with computers", architecture search is computers replacing data scientists. $1.2M is roughly 3-4 data scientists' annual compensations at a company like Google or Uber.
Finding hyperparameters for an existing architecture is much easier because you would typically deal with a much lower cardinality in hyperparameter space. SigOpt is helping with that. Google has an internal solution that is able to take advantage of parameters within their job scheduling infrastructure (they actually have a bunch of them, the one I'm talking about is called hyperband [0]). CERN, as far as I know, was using hyperopt [1]. Avant uses an open-source version of SigOpt that we wrote in 2016 called loop [2].
[0] - https://arxiv.org/pdf/1603.06560.pdf [1] - http://hyperopt.github.io/hyperopt [2] - https://github.com/avantoss/loop