How to Become a Machine Learning Engineer in 2023

Machine learning engineers work with data, artificial intelligence, and algorithms. This position is not an entry-level job, but you can take steps to move into a successful and rewarding career to become a machine learning engineer. In this career, candidates will use artificial intelligence to adopt and predict outcomes by analyzing data. Those who choose machine learning engineering as a career can expect to see tremendous job growth in the next few years. If you want to learn more about a career as a machine learning engineer and how to reach that goal, here are a few steps to follow.

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What Is Machine Learning?

Machine learning is an aspect of the computer science field focusing on artificial intelligence. This career will use computer algorithms to interpret data, replicating how humans learn and process information. The machine learning engineering field can include everything from facial recognition to video surveillance. Recently, customer-facing businesses have used machine learning to understand their customers’ preferences and patterns to create or design ad campaigns and direct marketing materials.

Even social media platforms, like Facebook, have used machine learning to target advertisements based on the users’ preferences, such as posts and likes on the website. Along with that, some shopping websites, such as Amazon,  use an algorithm to suggest items to purchase based on the customer’s viewing history and past orders. 

Machine learning works by breaking out the learning system of machine-based algorithms into three sections:

Decision Process

These machine learning algorithms are used to make a classification or prediction. The algorithm creates an estimate of the data’s pattern based on input data that can be unlabeled or labeled. 

Error Decision

With this function, this step evaluates the model’s prediction. If there is an unknown example, then the error function can compare to assess the model’s accuracy.

Model Optimization Process

If the model has better data points in the training set, then the engineer can adjust the weights to reduce any discrepancy between the model estimate and the known example. The algorithms often repair the “evaluate and optimize” process by updating the weights until the accuracy threshold has been met. 

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What Does a Machine Learning Engineer Do?

Before embarking on this career path, you will want to know the job responsibilities of a machine learning engineer. These individuals are critical members of the data science team. Many of the day-to-day responsibilities include researching, building, and designing artificial intelligence for machine learning. Along with that, these individuals maintain and improve the existing article intelligence systems. 

The machine learning engineer also acts as a crucial communicator between the data science team members. These engineers often work in close contact with other data scientists to develop a model for building artificial intelligence systems. Those who construct and run the artificial intelligence system will also work closely with machine learning engineers. 

Many of the job responsibilities for machine learning engineers will vary, but some of the most common duties include the following:

• Running artificial intelligence tests and experiments
• Implementing machine learning algorithms
• Developing and designing machine learning systems
• Performing statistical analysis

Job Opportunities for Machine Learning Engineers

As technology evolves, so do the job opportunities for machine learning engineers. Over the past decade, the computer science field has flourished. Computer science research jobs are growing rapidly per the Bureau of Labor Statistics. These jobs have an expected growth rate of 22% through 2030. The medium annual salary for a machine learning engineer is $126,830.

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Job Outlook

In 2019, Indeed named machine learning engineer as the top job of the year. The ranking was based on the job listings related to the artificial intelligence and machine learning field over the past three years. Since the COVID-19 pandemic has refocused how businesses operate and manage their workforce, there has been a greater demand for the automation of routine tasks and jobs. In those situations, the machine learning engineer is quickly becoming a sought-after career in the data science industry. 

The salary potential for machine learning engineering is also high. Like most computer science and high-level technology careers, machine learning engineers will earn a salary above the national average. Almost all machine learning engineers can expect to have a salary in the six figures. As of 2022, the average base salary was listed as $120,549 for a machine learning engineer.

How To Become a Machine Learning Engineer

If this position sounds like a dream job for you, there are several steps you can take to make machine learning engineering a career choice. In many situations, working your way up through the data science field to become a machine learning engineer is possible. Here are a few steps to take for this rewarding career. 

#1 – Earn a Bachelor’s Degree in Computer Science or a Related Field

Since machine learning is related to the computer science field, potential engineers will need a strong background in data science, computer programming, and mathematics. Many machine learning engineering positions will require the candidate to have a bachelor’s degree. If you are interested in this career, interested individuals will need a degree in computer science or another related field, like statistics, as a solid foundation for their future. 

#2 – Gain Entry-Level Work Experience

After earning a computer science degree, candidates will need to start working in the data science field to gain experience working with artificial intelligence or machine learning. Many of these lower entry positions can help candidates make connections and gain experience to further their career in machine learning engineering. Some entry-level positions include:

• Software engineer
• Data scientist
• Computer engineer
• Software developer

#3 – Earn an Advanced Degree

Working in the artificial science and data science field with just a bachelor’s degree is possible, but your career options may be limited. Pursuing a master’s degree in data science, computer science, or software engineering can help you complete complex tasks that are a part of a machine learning engineer’s daily activities. Along with that, an advanced degree will give you some leverage to apply for other jobs in the field. 

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Get Started on Your Machine Learning Engineer Career

Machine learning and artificial intelligence are rapidly growing in the fields of data and computer science. While becoming a machine learning engineer will take years of education and experience, you can start on the right path today. By building your knowledge of software development and programming languages, you can earn higher learning degrees and certifications to prepare you for the machine learning engineer job. This position requires a lot of hard work, but taking those first few steps can lead you to a rewarding career. 

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