Before thinking about what a machine learning engineer does, we need to know what machine learning is! Machine learning is a way to train machines to learn from data and make decisions about new data they come across. It uses statistics and data science to begin to learn things without being told what to do by a programmer or engineer.
Examples of machine learning (ML) are:
- Netflix recommends movies to you based on what you have previously watched
- Facial recognition to unlock your phone
- Bank fraud detection
To learn more about what machine learning is, check out this video:
What is a machine learning engineer?
So we know what ML is, but what does a machine learning engineer do? ML engineers are part of a team that research, analyse, and build AI algorithms that are able to learn.
These engineers work on designing, researching and implementing ML algorithms. They are likely to work with data scientists in the company to identify the right data to use and what models work best.
Why is it so in demand?
There’s a huge number of companies that are looking to hire ML engineers, especially tech companies and those working in social media, like Apple, Twitter, or Tiktok. Think about the recommended videos you see on your social media based on what you spend your time watching and liking. This is all down to ML! It learns what kind of things you like and react to more and recommends things that match similar criteria to that content.
It’s not only tech companies that need ML engineers. It is used in recruitment, education, healthcare, and increasingly more and more fields. Think about any role where information has to be analysed and categorised… ML offers us technology that can sort this much faster than a human being.
How do you become a machine learning engineer?
Most ML engineer roles require you to have a degree, but there’s a range of degrees that could qualify you, including:
- Computer science
- Electrical engineering
What skills do you need to be an ML engineer? A good understanding of data is key! ML engineers work with data and AI daily so it’s important to be comfortable using data and programming languages.
The most common programming languages used are Python, C++, and Java, but you will be able to adapt and learn different languages that you need.