how to become a machine learning engineer (2022 Guide)

Is Machine Learning a Good Career?

BrainStation’s Machine Learning Engineer career guide is intended to help you take the first steps toward a lucrative career in machine learning. Read on to learn whether or not machine learning is a good career path.

Become a Machine Learning Engineer

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Yes, machine learning is a good career path. According to a recent report by Indeed, Machine Learning Engineer is one of the top jobs in the United States in terms of salary, growth of postings, and general demand.

Since 2015, the number of postings for Machine Learning Engineer have increased roughly 350 percent with the base salary reaching more than $140,000.

If you’re excited about data science, automation, and algorithms, machine learning is the right career move for you. Your days will be filled with moving large amounts of raw data, implementing machine learning algorithms to process that data, and then automating the process for optimization.

Another reason a career in machine learning is so appealing? There are so many career paths machine learning professionals can choose to take within the industry. With a background in machine learning, you can get a high-paying job as a Machine Learning Engineer, Data Scientist, NLP Scientist, Business Intelligence Developer, or a Human-Centered Machine Learning Designer.

Part of the reason these positions are so lucrative is because people with machine learning skills are in high demand and low supply. There have even been reports of bidding wars over artificial intelligence (AI) talent as tech giants rush to secure the top minds in the industry.

Machine Learning Engineer Career Paths

Few tech professionals begin their careers as Machine Learning Engineers. Most who eventually pursue jobs in machine learning switch over from a role like Software Engineer, Software Programmer, Software Developer, Data Scientist, or Data Engineer.

The two most common career paths to becoming a Machine Learning Engineer often wind through data or software development, though that does require fairly significant experience with programming languages. A machine learning professional who starts in development might study computer science or attend a coding bootcamp to build out those coding skills.

Once someone has a few years of experience in a machine learning career, they could start applying for more senior-level machine learning jobs or they could choose to specialize in niche roles relating to data, automation, cloud computing, and deep learning.

For instance, demand is currently high for tech professionals who specialize in natural language processing – look for roles like NLP Scientist or NLP Engineer – while Human-Centered Machine Learning Designer is another role that could appeal to someone with advanced machine learning knowledge.