How to Become a Machine Learning Engineer in 3 Steps

Are you considering a career as a machine learning engineer but unsure of where to start? The road to becoming a machine learning engineer can be interesting and gratifying, despite the fact that this tech career isn’t entry-level.

A fascinating area of artificial intelligence called machine learning includes anticipating and changing results as new data is gathered. Machine learning engineers witnessed a 344 percent increase in job listings between 2015 and 2018, making it the top position in 2019. As machine learning has continued to be used by a variety of businesses, we may assume that this growth has continued since 2018.

Machine learning skills encompass everything from smartphone facial recognition to video surveillance. However, companies that deal with customers also use it to comprehend consumer trends and preferences and create direct marketing or advertising campaigns. Engineers who specialize in machine learning skills play a crucial role in the data science team. In addition to maintaining and enhancing current artificial intelligence systems, their jobs include investigating, developing, and designing the artificial intelligence that powers machine learning.

A machine learning engineer frequently works closely with the data scientists who create the models for creating AI systems and the individuals who create and manage them. They also play a crucial communication role with other members of the data science team.

You can advance to the position of machine learning engineer. You must complete these three phases of skills required to become a machine learning engineer.

1. Complete a bachelor’s program in computer science or a closely related discipline.

Success in machine learning depends on having a solid foundation in computer programming, data science, and mathematics because it is a subfield of computer science. A bachelor’s degree is typically required for machine learning engineering positions, thus starting a course of study in computer science or a closely related subject, like statistics, is a suitable first step.

2. Acquire experience in entry-level jobs

The next step after receiving a computer science degree is to begin working in the data science industry in order to obtain expertise with machine learning or artificial intelligence. Some entry-level jobs that can lead to a career in machine learning skills include Developer of software and data science and computer programmer.

3. Obtain a graduate degree

Even while you can work in artificial intelligence and data science with just a bachelor’s degree, getting a master’s or doctorate in computer science, data science, or software engineering will assist you to grasp the more difficult jobs that machine learning engineers must performing. Additionally, it will help you when you seek jobs, particularly if you have supplemented your education with numerous internships.