How to Become a Machine Learning Engineer

If you are curious about what it takes to become a Machine Learning Engineer, this article is a good place to start. Unsurprisingly, you’ll want to explore different training options and ensure that you are receiving the most thorough education possible. Many might assume that it is necessary to obtain a degree to become a Machine Learning Engineer, but that is not the case. You’ll want to find a reputable education provider because there are many different tools, skills, and qualities you’ll want to acquire before considering yourself an expert Machine Learning Engineer. With determination and proper guidance, you can take the next steps in your professional journey to becoming a Machine Learning Engineer.

What is a Machine Learning Engineer?

A Machine Learning Engineer is a technical role that requires knowledge of artificial intelligence, mathematics, and data science. They are tasked with building and deploying machine learning systems that can automate tasks to make business operations easier. In addition, they manage those systems and continually update and enhance their models to maximize their efficiency. There are multiple skills a machine learning expert would have, including mathematics, analytics, coding, and communication. 

On an average workday, a Machine Learning Engineer will analyze data, develop models, and improve their previous systems. They will typically use their keen analytics skills to determine actionable insights that help make better decisions for the business. They will also document their progress to determine what collaborative efforts should be taken. Machine Learning Engineers work closely with similar professionals such as Data Scientists and Software Engineers.

Machine Learning Engineers can work in a traditional office setting and work on projects with others on the team or individually. However, they can also work remotely or in a hybrid setting, which requires some in-house work, such as attending meetings and other collaborative sessions. In addition, they can find freelance work and offer their skills to numerous clients for a short-term period. This career is expected to become increasingly necessary in the coming years as the reliance on data and technology grows.

What Tools Do I Need To Get Started?

You will need to learn certain skills and tools before becoming a Machine Learning Engineer. These are just a few of the most useful tools to have in your arsenal before applying to Machine Learning Engineer positions.

Coding Languages

You will need to know multiple programming languages to become a Machine Learning Engineer. In particular, Python is considered the go-to language because most machine learning is completed within its corresponding libraries and frameworks., In addition, JavaScript is incredibly useful to learn for artificial intelligence integration on web pages. Similarly, R is often used to assist with statistical analysis and data visualization. These programming languages are free to use and some do not even require installation. JavaScript, for example, does not require downloading. On the other hand, you’ll need to install Python on your computer.

Frameworks and Libraries

Machine Learning Engineers also know how to utilize different libraries and frameworks, particularly within Python. For example, Pandas is a Python library used for data cleansing and analysis. NumPy is a package that provides an array of mathematical functions. Similarly, scikit-learn is open-source and makes data transformation much easier. PyTorch, which allows users to develop mutable algorithms, is also commonly used. Its popularity is mainly attributed to how user-friendly it is. The frameworks that correspond with each programming language are as easily accessible as the languages themselves.

Data Visualization Platforms

For data visualization, many Machine Learning Engineers use Python libraries. For instance, Matplotlib is a basic plotting library for Python that visualizes data sets. In addition, Seaborn, which is built within Matplotlib, makes that data easier to understand and simplifies the statistical data. Plotly allows Machine Learning Engineers to create interactive dashboards. However, some may choose to learn other tools of data visualization, such as Tableau, Power BI, or Google Charts. There are public versions of Tableau that are free to use, and many coding languages (Python included) are open-source, so they are highly accessible and entirely usable.

Collaborative Tools

Because Machine Learning Engineers work closely with other professionals from time to time, they will often use platforms like Slack or Microsoft Teams to collaborate on different projects. They are also useful for sharing and storing documents and keeping in close communication as there are various messaging features. Slack is free to download and requires users to sign up to make an account. Microsoft Teams, however, has a free version that has slightly fewer features than the paid version.

Steps to Become a Machine Learning Engineer

You will want to take a few key steps to become a Machine Learning Engineer. First, you’ll want to sharpen your mathematical skills in subjects like linear algebra, statistics, calculus, and probability theory. You will also want to learn myriad programming languages, such as R, Python, and Java. Beyond the specific skills, you’ll want to understand the theory and fundamentals behind machine learning, such as neural networks and deep learning architectures. Above all else, you’ll want to find a reputable training method from which to learn these essential skills.

Taking individual classes, bootcamps, or certificate courses in machine learning is one of the best ways to learn these skills. Not only are they flexible and easily accessible, they provide students with practical experience that will translate easily in the workplace. Enrolling in online courses like those at Noble Desktop allows you to explore different topics, gain base-level skills in relevant subjects, and practice the day-to-day tasks of a machine learning expert firsthand. The hands-on projects you complete in class will give you a glimpse into the field, and you’ll feel supported throughout with the help of an expert instructor. You can choose between lengthy courses or short courses, as well as beginner and advanced levels. This is truly one of the best ways to learn because the courses are customizable to your needs and help you develop professionally.

Noble Desktop offers certificate courses, bootcamps, and short courses on myriad subjects relevant to machine learning. You can explore certificates in data science and generative artificial intelligence or bootcamps in specific coding languages such as Python. In addition, their short courses range in subject matter and are typically completed within a day or so. Noble Desktop also offers students different benefits such as payment plans and the choice between full-time and part-time instruction.

Machine Learning Engineer Career Path

A career in machine learning engineering requires some level of educational training relevant to the preferred skill set. This can entail pursuing a degree from a university, but that is not the only choice. Every week, a Machine Learning Engineer may be found building models or maintaining previously deployed models. They collaborate with other software and data professionals on different projects and can specialize in a particular area, such as deep learning. This is an increasingly popular field that shows no signs of slowing. In addition, there are many opportunities for advancement in this field, as more time and experience can lead to senior-level positions.

Regardless of the industry, a Machine Learning Engineer is an extremely valuable position to hold. They play a vital role in improving business practices, optimizing efficiency, solving important logistical problems, and making more well-informed business decisions. They offer skills that very few other tech professionals can by designing and maintaining machine learning models made for automation. Their advanced mathematical and analytical skills, paired with their critical thinking and problem-solving skills, make them invaluable members of any team.

There are many ways to work as a Machine Learning Engineer as well. If you prefer the lifestyle of a freelancing professional, you can explore ways to become a freelance Machine Learning Engineer. In addition, remember that although a degree is necessary, it is not the only way to become a Machine Learning Engineer. You can become a Machine Learning Engineer without a degree by exploring different training options that offer thorough, hands-on experience with the tools and tasks you’ll encounter as a Machine Learning Engineer.

Why Become A Machine Learning Engineer?

A career as a Machine Learning Engineer is a fantastic path to take for numerous reasons. Firstly, there is a high demand for the position. As businesses increasingly rely on data and artificial intelligence, the field will only see growth in the coming decades. In addition, this is a relatively flexible career path that offers full-time and part-time positions as well as in-office, remote, or hybrid work. You can also find freelancing opportunities for machine learning. Overall, this is a lucrative job that affords many professional development opportunities and areas for growth. 

Additionally, the work a Machine Learning Engineer puts forth is important and impacts different industries and companies tremendously. Most Machine Learning Engineers work on projects that help solve real-world problems and improve healthcare treatment methods, secure financial information, or enhance supply chain management operations. In essence, Machine Learning Engineers make their mark on the world and help contribute to highly rewarding projects.

Machine Learning Engineers also gain a wide set of skills that are transferrable across different positions and industries. With ablend of technical, creative problem-solving, and interpersonal communication skills, a Machine Learning Engineer can consider themselves a well-rounded tech professional. With the constant changes seen in the market and the tech space, there is always something new to discover. If you have considered becoming a Machine Learning Engineer, it is a worthwhile endeavor. The dynamic role is high-paying, professionally fulfilling, and immeasurably important to the success of any company. As such, there are many reasons to become a Machine Learning Engineer.

Learn the Skills to Become a Machine Learning Engineer at Noble Desktop

If you are interested in becoming a Machine Learning Engineer, there are many ways to start your journey. Notably, you can explore certificate programs at reputable training centers such as Noble Desktop. Their Data Science Certificate covers all the necessary skills to become a data science professional, which is the field where machine learning practices are regularly applied. Specifically, students will learn relevant coding languages, automation, machine learning, data analysis, and predictive modeling skills. Throughout this 114-hour course, students will learn how to clean, balance, and apply machine learning algorithms to data sets with scikit-learn. In addition, they will practice analyzing data with Python libraries like NumPy and Pandas. By the end of the course, students will be able to automate everyday tasks and utilize their skills in the data science field. Noble Desktop provides students with additional benefits to support them through their learning journey. In this course, students can access 1-on-1 mentoring sessions, a free retake, and various payment plans. Upon completion, they will earn a verified digital certificate that displays their mastery of the material.

Likewise, Noble Desktop offers a Software Engineering Certificate where machine learning skills and relevant information will be discussed. In this certificate course, students will learn to use Python and Django for machine learning algorithms and task automation. In addition to Python, they will learn to build the front end of a webpage with HTML, CSS, and JavaScript, which all add interactive functionality. This course also gives students the exposure and experience they need to develop a professional portfolio with their completed projects. Over 510 total hours, students can access myriad benefits like a course retake, bonus mentoring sessions, and an additional elective course, all at no extra cost. Once the students complete the program, they will earn their verified certificate to show for all their accomplishments.

To gain more knowledge of artificial intelligence for business purposes, consider the Generative AI Certificate from Noble Desktop. In this 78-hour course, students will learn how to utilize artificial intelligence in different work settings and for varying reasons. For instance, students will learn how artificial intelligence can help automate workplace tasks or quickly analyze large data sets. The instructor will guide students through projects that leverage artificial intelligence for different marketing strategies and help create high-quality marketing designs. This course does not require any previous coding experience and is solely meant to delve deeper into the larger implications of artificial intelligence and its usefulness in the workplace. Through hands-on projects, students will gain the necessary experience to apply the skills in their field. Students can retake the course anytime within a year of their original enrollment at no additional cost. Plus, Noble Desktop will award students with a digital certificate once the course ends.