So, you want to build your career in the next big thing, actually, the biggest phenomenon to sweep the world since the Internet.

Welcome, but you’re not alone. Millions of aspirants across the planet are gearing up their skills and knowledge, getting accredited and certified in the sexier-than-sexiest career of the 21st century (sorry, Harvard Business Review). So what will set you apart? For starters, knowing what you’re getting into:

What an Artificial Intelligence Engineer Actually Does

An artificial intelligence engineer conceptualizes, designs, builds and finally rolls out sophisticated machine learning algorithms that facilitate autonomous knowledge gathering through unstructured training sets (deep learning) besides the deployment of the AI models in real-world production setups. AI engineers also set up the basis of intelligent automation processes using proprietary or third-party tools within the enterprise. Other functions include researching and recommendations on improvements in existing machine learning algorithms, SDLC based machine learning implementation on a dataset to train the model, data mining, pattern recognition and training of the AI model, and the training of ML-based algos for domain-specific functions, some of which are already mentioned above.

While these are the core functions, at an entry-level, most AI engineers can expect to start at the bottom rung of the AI/data science ladder with munging large datasets, while also training AI models for various functions including multilayer neural networks, computer vision and other similar human-intensive functions. But it is important to remember, however, that this is just the beginning and has the potential to culminate into a principal or head AI engineer role as your career progresses.

https://www.artiba.org/blog/the-artificial-intelligence-engineer-career-roadmap-all-you-need-to-know