Five Steps to Become a Machine Learning Engineer

With digitalization and Artificial Intelligence at their peak, the machine learning field is being hyped more than ever. This is very much understandable as the future holds immense value for every machine learning engineer and other similar professionals. So, who is a machine learning engineer? And what do they do? Let’s get into the details.

What is a machine learning engineer and what do they do?

A machine learning engineer is someone who collects data via research and uses the same to either build or design a system based on artificial intelligence. These engineers are found generally in the Information Technology sector. The professionals team up with data scientists, data analysts, data engineers, administrators and data architects. Although the education and procedure might look simpler on the outside, not everyone becomes a machine learning engineer. The reason behind this is a lack of knowledge of taking the right steps along with the right areas to work on. Therefore, we bring you a complete guide on how you can escape it all and choose to be one of them.

Five Steps to Become a Machine Learning Engineer

To be a machine learning engineer, one should follow the following steps-

1. Make yourself aware of the fundamentals of software engineering.

Machine learning engineers have to code for a huge amount of systems to get things going. Hence, it becomes important for an aspiring machine learning engineer to learn various coding languages, especially the updated and trendy ones to start well with. This might include Python, C++ and more similar languages. 

2. Learn the basics of data science. 

Although machine learning engineers work as a team with data scientists, it is important to have a bit of knowledge regarding the same to cooperate and work better. One of the major differences that separate machine learning engineers from regular software engineers are the fact that they can go well with data scientists. They act as a bridge between the data and the action that is between the systems of AI and data scientists. 

3. Make yourself familiar with important concepts and tools. 

Along with learning the fundamentals of software engineering and coding, it is also important to get some practical knowledge regarding inside concepts of machine learning. As doctors and lawyers have their conversing ways, so do machine learning engineers. Hence, it’s important to get comfortable and familiar with that too. 

4. Get some real experience.

This can be an internship or a small project or a job at some firm. Start working on some real-life assignments to gather some experience to get started a good way. The reason this step is important is that in the future, the same experience can be presented well in your portfolio which might help you get your dream job easily.

5. Opt for a course.

To be good at something, keep learning. Opt for a course. It can be available in a wide range of courses like a data science course or an artificial intelligence course etc. You can either opt for these to learn and then apply for it. There are several online as well as offline courses to support machine learning today. 

Apart from these 5 steps, some machine learning engineers also hold a degree in the same while others claim to have good mathematical as well as statistical skills. You can also go for some books like “Clean Code” by Robert, “Deep Learning” by Ian or “The Pragmatic Programmer” by David etc. As the machine learning field is vast and enormous, you can choose all sorts of learning mediums like blogs, videos, podcasts. Make sure you don’t miss out on any information and practice hard.