The Most In-Demand Tech Skills for Machine Learning Engineers
How are machine learning engineers different from data scientists and data engineers?
In this article you’ll see new research that shows the most popular technology terms in job listings for machine learning engineers. 📊
We’ll explore how machine learning engineers fit into the flow of data in an organization. Finally, I’ll share a suggested learning path for machine learning engineer skills.
Machine learning engineer is a hip-sounding job title and people in the role are well compensated. According to one analysis , it was the top emerging job on LinkedIn between 2012 and 2017. Indeed reported an average salary of $140,536 for machine learning engineers in the US as of June 26, 2020. Not too shabby. 😀
Let’s look at how machine learning engineers fit into the flow of data within an organization.
Data Flow in Organizations
Here’s a representation of how data flows through an organization.
Data is generated, ingested, and stored in databases. The data might be modified to make it more usable through ETL, which stands for extract, transform, and load.
Then the data can be used to make machine learning models, do inference, and create analyses.
If the data is used in machine learning models, then those models might be served to the word through websites or APIs. That’s the path on the left. 📱
Alternatively, if the data was procured with the intent of establishing causality — often through experimentation — then statistical analysis can be performed and shared. 🔬
Finally, if the data is used in post-hoc analysis to glean insights, it will likely be fed into a report or presentation. 🖥
Let’s add the roles that often accompany the flow of data to our diagram.
