Machine learning is at the core of some of today’s most cutting-edge technologies, from recommendation algorithms to self-driving cars. And it’s machine learning engineers who are largely responsible for making this happen. Machine learning engineers can work across a broad range of industries, so long as there is data to be collected and analyzed. Unsurprisingly, the systems that machine learning engineers build can be as varied as the industries they serve.

For example, consider a social media network like Twitter, which can use its user data to provide users with the best experience possible. To do this, Twitter needs to understand what kind of material its users are viewing and how they interact with it. A machine learning engineer helps design the systems that work with these data sets.

What to find out how machine learning engineers do this? Then you’re in the right place. Below, we’ll tell you all about what a machine learning engineer does.

What Is Machine Learning?

Machine learning is the process of employing algorithms to take in and interpret data, transforming it into something that is usable for their given industry. Machine learning is primarily used by increasingly digital enterprises, such as smartphone applications and streaming services, though it can be employed at the ground level for various commercial properties.

Advertising, for example, can use data discovered through machine learning to better reach its customers. While it’s best used for digital advertising on social media platforms, the insights generated through machine learning are applicable across multiple spheres. Indeed, there is almost no industry that exists in the modern, digitally-driven market that can’t take advantage of machine learning in one way or another, making it one of the most valuable skills to develop.

Working as a Machine Learning Engineer

Due to the extremely flexible nature of the work, it is almost impossible to pin down a definite picture of what it’s like to work as a machine learning engineer. Many large companies, such as Amazon or Twitter, rely on machine learning techniques and big data in general to improve their business, but how they go about this depends on their needs.

Nonetheless, a machine learning engineer can at least expect some commonalities in their job description. You’ll be expected to work alongside others who work with data, and you’ll need to be able to present your findings in a clear and concise way to shareholders. You’ll be expected to understand how to handle and use data in one form or another, and ultimately your work is likely to be judged based on the machine learning applications you develop to meet your company’s needs.

Machine Learning Engineer Salaries

According to Indeed, the average salary for a machine learning engineer is around $118,000. This, of course, varies as much as the work that is expected, so you can expect less for an entry-level position. Keep in mind that $118,000 is simply the average, and does not necessarily include additional compensation (such as bonuses or stock options), which can be quite lucrative in some industries.

Machine Learning Hard Skills

A machine learning engineer typically needs to have a number of technical skills in order to succeed in the industry. First, an understanding of data science is a requirement for machine learning engineers. Most engineers have a full understanding of several coding languages, including Python, C++, Scala, and more. Using this code, a data engineer should be able to sort data and build algorithms that can work with databases. Similarly, you will be expected to be able to design a variety of data models, ultimately with the goal of being able to provide actionable information for stakeholders.

In addition to an understanding of data science as a whole, software engineering skills go a long way to overall success in the industry. You’ll be expected to build machine learning programs, and will also need to be able to work within computing architectures of all kinds. Similarly, you’ll need to be able to work with and translate several data structures, including complex stacks and data arrays.

Machine Learning Engineer Soft Skills

In addition to the technical, hard skills expected, most machine learning engineering roles also require soft skills too. Many of the roles within a machine learning engineer's purview require that you work directly with others, meaning you must have capable communication skills. Similarly, you should be able to manage your time, work well within a team structure, and otherwise develop interpersonal skills. You’ll also often have to manage your own output, so making sure you can complete tasks in a timely manner is key.

Machine Learning Career Paths

As a machine learning engineer, you’ll be expected to have all the skills already noted above, so you can apply your data modeling expertise to build an artificial intelligence architecture that will serve your employer.

However, many machine learning experts instead pursue a career in applied machine learning, which is often more of an evaluative role. These individuals review systems that are often already in place, building on existing applications and improving on them, essentially further refining algorithms. Finally, many who pursue a career in machine learning ultimately become software engineers, designing systems that are designed to take in and employ data rather than working with the architecture that surrounds them.

The Premier Machine Learning Bootcamp

If you’re interested in becoming a machine learning engineer, one of the best ways to start your career is by signing up for a machine learning bootcamp that will teach you the ins and outs of the industry. The University of California at San Deigo’s Machine Learning Engineering and AI Bootcamp is one of the best in the nation, and helps launch its students into the field through its career support services. Sign up today to join this rewarding, lucrative industry.