Data Scientist vs Machine Learning Engineer
Have been thinking changing jobs recently. For future development, which one has more potential, DS or MLE?
MLE roles will continue to be popular for a while until the market realises that 99.9% of tech problems can be solved by traditional SWE roles.
They will keep being popular. Programming will be to the next century what writing was in the 19th. “SWE” will make as low sense to someone in 50 years as “typewriter” as a job role makes sense to us today.
I hope I’m wrong since your vision of the future is infinitely less dreary than mine but I find that unlikely.
Thanks for reply. Looks like MLE is more popular.
To deploy an ml model requires a fair amount of software engineering.
DS are, well, scientists. They should be savvy with experimental design and causal analysis that drive large-scale strategy. A priestly caste. MLEs are the manual labor for implementing the DS’s insights at scale. Important, sure, but theoretically a little more proletarian
Are you currently a DS at facebook?
Very few DS are actually the priestly caste. Most DS today think they’re Python devs because they write SQL in pandas and they’re statisticians just because they import sklearn. Most of these “scientists” are glorified consultants a la McKinsey. MLEs are also hyped but their understanding of scale, systems and production (a term foreign to most DS) is a transferable skill set when the ML bubble finally bursts. So it’s better to be in that bucket.
Data science has good potential if it's what was called data science 5-years ago. Companies are increasingly calling those positions MLE, applied scientist, or research scientist though, while using the data scientist title only for analyst. So don't be a data scientist that is actually just analyst. If you're building and deploying models that have impact, then you have a clear path for growth though.
They require two separate background: You need a PhD or at least be very good at research & experimentation to get far in DS. You need to understand ML principles and be good at coding to get far in MLE.
Ds is business facing, mle is not. If you know anything you know who has most room for growth based on that.
Software engineer with an ML focus is probably better
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Potential depends on who you are in this case. DS has you talking to execs now and again, MLE is a SME on an engineering team. The first has more support to move up, the second slightly higher pay at the ground level.
Correct assessment, though I believe the pay is much higher on average for the MLE at ground level
Are’s they basically the same?
Data scientist = analyst, MLE = SWE
Depending on you define DS. Most of Data Scientist deploy machine learning model nowadays.