This article explains the difference between AI (Artificial Intelligence) Engineers and ML (Machine Learning) Engineers in a simplified form.
AI Engineer Definition
An engineer who uses AI to solve real-world problems (Software engineer that uses AI integration to their applications). For example, they could build an app, that uses AI, that allows to clean up emails for employees.
AI Engineers tend to work on collecting data and improving their model for it to perform better and accurate in addition to just coding.
ML Engineer Definition
An engineer with the focus on building and designing machine learning systems for AI.
In other words, they build the model itself by working with the data science team to collect data and improve ML algorithms. For example, the…
This article explains the difference between AI (Artificial Intelligence) Engineers and ML (Machine Learning) Engineers in a simplified form.
AI Engineer Definition
An engineer who uses AI to solve real-world problems (Software engineer that uses AI integration to their applications). For example, they could build an app, that uses AI, that allows to clean up emails for employees.
AI Engineers tend to work on collecting data and improving their model for it to perform better and accurate in addition to just coding.
ML Engineer Definition
An engineer with the focus on building and designing machine learning systems for AI.
In other words, they build the model itself by working with the data science team to collect data and improve ML algorithms. For example, they can build a model that classify images and the AI engineer use that model for their application.
Difference from AI Engineer and ML Engineer?
What is Similar?
Knowledge of Computer Science and having the methodologies as a Software Engineer such as knowing best practices of building products in a business standpoint for example. Having a Bachelors in Computer Science is all you need (Depending on the courses you took) but having a Master’s does help.
Python (Main language), Java, and R. Libraries such as NumPy, Pandas, TensorFlow and Pytorch are used.
Of course, to know AI, you need to know Machine Learning. AI is a broader scope. Machine Learning is PART of AI. Diagram shown below.
What is Different?
- You needs to have a good mathematical background, specifically in calculus, and linear algebra when it comes to Machine Learning in general. For AI, I tend to think as an "All-around" where it is not necessarily required, but it is helpful to become an AI Engineer Expert.
- On top of the first point, Machine Learning is tend to be more research focus when it comes to improving algorithms and model performance while AI Engineer are more building the products with existing AI models made by Machine Learning experts.
This is my simplified version of the difference between AI Engineer and ML Engineer. Note that this covers only the simple definitions and comparing the two. If you would like to learn more, I have provided references I used into writing this post below. If you have any suggestions on improving my writing or anything I should add, feel free to leave a comment!
References: https://www.simplilearn.com/tutorials/artificial-intelligence-tutorial/how-to-become-an-ai-engineer
https://www.techtarget.com/whatis/feature/How-to-become-an-artificial-intelligence-engineer
https://resources.workable.com/ai-engineer-job-description
https://www.indeed.com/career-advice/finding-a-job/ai-engineer
https://www.codecademy.com/resources/blog/what-does-an-ai-engineer-do
https://www.coursera.org/articles/what-is-machine-learning-engineer
https://michael-lyamm.medium.com/ai-engineer-vs-ml-engineer-key-differences-c4d5c9838361