Machine learning and artificial intelligence are currently the hottest trends in IT and almost every company is on the lookout for a proficient machine learning engineer. With it ranking as one of the most in-demand jobs with an attractive average salary to match, it’s not surprising why this is the case.
When most people hear of the phrase: “machine learning,” they instantly picture a highly skilled engineer programming insanely smart robots planning to take over the world. However, this is far from being the case, as machine learning is a lot less complicated than what the media make it seem.
In this article, you’ll get a realistic outlook of what machine learning engineering looks like in the real world and how to become one. Also, you’ll learn some of the roles and responsibilities of the average machine learning engineer to know what your potential workday will look like.
Machine Learning Engineer Job Description
Machine learning engineering is just what it sounds like; a career that involves the study and design of self-sustainable artificial intelligence programs that learn to become smarter. A machine learning engineer typically works with humongous data sets to create AI capable of learning on its own.
Some of the practical applications that a machine learning engineer might be required to work on include algorithms that predict movies and videos like the algorithm that tailors the content on the first page of platforms like YouTube and Netflix.
While those represent the fundamentals of organizational machine learning engineering, some of the more advanced applications of machine learning include self-driving vehicles, virtual assistants, medical diagnosis systems, and automatic language translations.
Of course, the average machine learning engineer will not be tasked with all the jobs described above.
Roles and Responsibilities of a Machine Learning Engineer
Your specific task will depend on the organization you’re working for, but you should expect to work with huge amounts of data and plenty of algorithms.
As hinted in the description above, the specific responsibilities of a machine learning engineer will depend on what company they’re working for, and how high up their position is. However, there is a general expectation for the tasks of the average machine learning engineer that you can use as a benchmark.
Here are some of the most common roles of a machine-level engineer in the average organization in the US or Canada.
- Developing machine learning algorithms
True to the job title, a machine learning engineer will usually be tasked with developing self-sufficient algorithms that can learn using data to help the company become more efficient. If you’re working at a big tech company, you’ll find yourself developing new algorithms or perfecting existing ones most times.
A perfect example of such a company is Google. Since the YouTube homepage is different for every Google user, it will be largely inefficient and tasking to have real people decide what videos show up on the homepage of every individual YouTube user, leaving the job to several machine learning algorithms.
- Using real-world data to improve existing machine learning models
Humans still have a long way to go before achieving true artificial intelligence. We still need to feed computers a truckload of data to make them smart enough to achieve minuscule tasks autonomously.
In case you’re previously unaware, a machine learning engineer is usually required to select the best datasets to train machine learning models. Firstly, they use their knowledge of statistical analysis to determine the best kinds of data to train the ML models and feed the data to the machine at will.
- Reviewing the practical uses of machine learning
An expert machine learning engineer can tell perfect use of a model when they see one. Understandably, it’s usually part of an engineer’s job to review the existing practical applications of machine learning to select what models are most probable to succeed.
However, it’s important to note that most people that face these kinds of tasks are the top guns in the industry. An entry-level machine learning engineer will be busier trying to build an ML model that the senior engineers can review to determine its probability to succeed down the line.
Academic Requirements for Machine Learning Engineering
While you don’t explicitly need a college degree to land a job as a machine learning engineer, there are only a few companies that would be willing to employ someone with no formal education. Thus, it’s important to try bagging a college degree before acquiring the related technical skills to land a job.
The first step to getting started with your newfound career is taking a foundational course related to computer science, mathematics, or statistics. If you can get admitted to an organization that offers data science as a course, it’s the no-brainer course for machine learning enthusiasts.
After your formal education, you should get hands-on experience with programming languages popularly used in the machine learning sector. The following section will list some of these languages as well as some technical skills you need to succeed in a machine learning engineering job.
Additional Skills for a Machine Learning Engineer
In addition to obtaining a related degree from a relevant university or college, there are many other skills to master before applying for your first job. While some of these skills can be acquired from boot camps and tutorials, learning-based internships are usually your best bet.
Firstly, you need more than average proficiency with some of the programming languages used in machine learning. These programming languages including Python, Scala, R, Java, and Lisp are all trendy in the machine learning world. Since you’ll be working with loads of data, learning database languages like SQL and NoSQL are also a must.
In addition to those, you’ll need excellent communication skills, critical thinking, problem-solving skills, and a curiosity that’s impossible to satisfy. When you get these nailed, you’re ready for your first job as a machine learning engineering job in the United States.
If you’ve ever wanted to change how YouTube recommends videos to you, this might be your chance. Choosing machine learning as a career may give you the possibility of working at the YouTube team with direct access to alter how the recommendation engine works.
While that’s just an instance, it simply shows you how powerful this career could be. If you’re considering choosing machine learning engineering as a career, this article is the ultimate guide to help you answer any questions you might have along the way.