The line between an AI Engineer and a Machine Learning Engineer can feel a bit blurry at first, and honestly, there’s some overlap but the day-to-day focus is where things start to differ. A Machine Learning Engineer is usually deep in the weeds with data, training models, tuning them, breaking them, fixing them you get the idea. Their world revolves around making models actually work well. An AI Engineer, on the other hand, tends to zoom out a little more they take those models and figure out how to plug them into real applications, whether that’s chatbots, recommendation systems, or something more complex involving NLP or computer vision. So while ML Engineers are building the brains, AI Engineers are often making sure those brains fit into a functioning system people can use. If you are trying to get into this space, starting with a solid AI and Machine Learning course makes a big difference, and from what I’ve seen, H2K Infosys is a pretty reliable option for practical, career-focused training.