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What are the typical roles and responsibilities of a large AI team?
Many AI teams will have Software Engineers in them. For example, for the smart speaker we need to write specialized software to execute on the joke or to set a timer or to answer questions about today's weather. Those are traditional software engineering tasks. So, it's not uncommon for AI teams to have enlarged fractions sometimes 50 percent, sometimes much much much more than 50 percent of Software Engineers in them.
The second common role is the Machine Learning Engineer. Machine Learning Engineer might write the software responsible for generating the A to B mapping or for building other machine learning algorithms needed for your product. They might gather the data of pictures of cars and positions of cars, train a neural network or train a deep learning algorithm and work iteratively to make sure that the learning algorithm is giving accurate outputs.
Another role is the Machine Learning Researcher. The typical role of the Machine Learning Researcher is to extend the state of the art in machine learning. Machine learning and AI more broadly are still advancing rapidly. So, many companies, for profit and non-profit, all have Machine Learning Researchers responsible for extending the state-of-the-art. Some Machine Learning Researchers will publish papers, but many companies also have Machine Learning Researchers that do research, but are less focused on publishing.
Applied Machine Learning Scientists live somewhere between Machine Learning Engineer and Machine Learning Researcher. The Machine Learning Scientists kind of does a bit of both. They are often responsible for going to the academic literature or the research literature and finding ways to adapt them to the problems they are facing: such as how to take the most cutting edge trigger word detection algorithm and adapt that to your smart speaker.
There are a lot of Data Scientists working in industries. The role of Data Scientist is not very well defined and the meaning is still evolving today. I think one of the primary responsibilities of Data Scientists is to examine data and provide insights, as well as to make presentations to teams or the executives in order to help drive business decision-making. There are also Data Scientists today whose work looks more like the Machine Learning Engineers.
With the rise of big data, there are also more and more Data Engineers whose main role is to help you organize your data, meaning, to make sure that your data is saved and is easily accessible, secure in a cost-effective way.
Finally, you'll also hear AI Product Managers. They help figure out what's feasible and valuable. The AI Product Manager has to do traditional product managers' roles in the AI era and they're needing new skill sets to figure out what's feasible and valuable in light of what AI can and cannot do today.
Because the field of AI is still evolving, none of these job titles are completely nailed down in the stone and different companies will use these job titles somewhat differently.

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