How to Become a Machine Learning Engineer in 2024?

Hello and welcome to this comprehensive guide on how to become a machine learning engineer in 2024. In this guide, we will take you through the steps, starting from educating yourself on this profession up to learning the required skills and finally getting your dream job.

What is Machine Learning?

But before we start, let’s clarify what Machine Learning is. Machine learning is possibly the single most transformative aspect of the broad domain of AI, enabling computational systems to learn from data and data-driven experience to make decisions.

Machine learning algorithms analyze enormous quantities of data and recognize patterns, predict, and adapt learning as human beings do.

Machine Learning engineer

Machine Learning Engineer’s Role

A Machine Learning Engineer is a trained expert who creates, maintains and deploys machine learning models and systems. In other words, these engineers blend data science and software engineering and work on the implementation of data-based insights into useful, viable applications.

The following tasks can undoubtedly be considered as part of a Machine Learning Engineer’s duties:

  • Data collection and preprocessing. When data scientists collect and clean data, engineers often work alongside them to make sure the data is appropriate for training ML models.
  • Model development. Creating machine learning models is at the heart of their job. They pick the right algorithms for the task, set the model’s parameters right, and test the model’s ability to make actual predictions and classifications.
  • Feature engineering. Engineers build features, or variables, that help a model better extract patterns from data, increasing its accuracy in predicting outcomes.
  • Model training. The final step is the training of the model, during which they feed the model with labelled examples and continuously retrain the model until it provides satisfactory results.
  • Model Deployment: After the training and validation model and model have taken place, engineers ensure it is accessible to end-users by deploying it into production environments. This step majorly involves attaching the model to a software system or application.
  • Monitoring and Maintenance: A machine learning model was already deployed, and any executing code needs to be under regular checks to ensure it is acting as anticipated in its real-world setting. Engineers are responsible for dealing with any operational issues at any time.

Steps to become a Machine Learning Engineer

There are steps to follow to enable one to become a machine learning engineer.

Step 1: Obtain the Necessary Education

Acquire the appropriate level of education Walk the path of obtaining a bachelor’s degree in computer science, mathematics, or close areas. To deepen my knowledge of the matter, many prospective Machine Learning Engineers end up acquiring a master’s degree or a PhD.

Step 2. Learn programming

Become proficient in multiple programming languages in the machine learning community, including Python, which is the most popular one.

Step 3. Study mathematics and statistics

Learn mathematics and statistics as well, as they serve as the basis for most machine-learning solutions and algorithms.

Step 4. Gain practical experience

Work on personal projects, online tutorials, and open-source projects to acquire some practical knowledge.

Step 5: Learn Machine Learning

Take online courses or get an education in machine learning and deep learning. There are courses available on Coursera, edX, Udacity, and many more.

Step 6: Build a Portfolio

Develop a personal portfolio with your machine learning projects to show to potential employers.

Step 7: Apply for entry-level positions

Apply for positions like Machine Learning Engineer internships or junior roles.

Step 8: Network and Stay Updated

Attend conferences, join the machine learning community and find a significant other to network with and learn from.

Salary of Machine Learning Engineer

Machine learning careers are particularly lucrative. Machine Learning Engineering is one of many high-level technology and computer science careers that pay several times the national average and total more than six figures. Indeed, the average Machine Learning Engineer’s base salary as of March 2024 is $162,740.


1. What is machine learning?

It is a part of computer science that deals with artificial intelligence specifically. It does this by using some algorithms in interpreting data in such a manner that, it mimics how humans learn. Thus, at the end of the day, the machine will improve its learning accuracy and therefore generate information based on this to the user.

2. What does a machine learning engineer do?

A skilled specialist who creates, builds and deploys machine learning models and systems is known as a Machine Learning Engineer. They can merge both data science and software engineering since they turn data-driven insights into practical, scalable applications.

3. What should I know to become a Machine Learning Engineer?

Programming skills, understanding of machine learning algorithms and theories, data modelling and evaluation, mathematics and statistics skills, data management skills, deep learning techniques, problem-solving abilities together with collaboration skills are just but a few required key expertise for an ML engineer.

4. What is the average salary of a Machine Learning Engineer?

As per Indeed’s report average base salary for a Machine Learning Engineer was $162, 740 as of March 2024.

5. How can I begin my path towards becoming a Machine Learning Engineer?

These are just a few steps you can take to become a machine learning engineer: obtain a bachelor’s degree in computer science or related discipline, pick up programming, engage with mathematics and statistics subjects, get involved in practical situations, study machine learning via online classes or formal education, put together a portfolio exhibiting your accomplishments and experiences, apply for beginners positions and connect with people who work in this domain.

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