How to Become a Machine Learning Engineer and Have a Lucrative Career

How to Become a Machine Learning Engineer and Have a Lucrative Career | Artificial Intelligence and Machine Learning | Emeritus

Machine learning engineers became the talk of the town in 2019 after Indeed named it the No.1 job in the US. In the same year, Gartner reported that most organizations were desperately looking for machine learning talent to kick off their artificial intelligence initiatives. There cannot be a better testament to the scope of machine learning as a career. And it certainly makes one wonder how to become a machine learning engineer. 

But before we get into the details of how to become a machine learning engineer, let’s do a quick recap of what the career comprises. 

What is Machine Learning?

Machine learning is a branch of artificial intelligence where computer systems learn to solve problems without explicit commands. Computers use algorithms and models that analyze and derive patterns from large amounts of data to make the system better at solving problems. 

Machine learning is an essential aspect of modern automation, where it predicts possible outcomes. Therefore, it is incredibly critical in data analytics and business intelligence. Machine learning applications include speech recognition, image processing, self-driving cars, product recommendations, and health monitoring devices, to name a few. 

Also Read: Artificial Intelligence vs Machine Learning: 5 Vital Points to Know

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What Does a Machine Learning Engineer Do?

Machine learning engineers are responsible for:

  1. Designing, building, and training machine learning algorithms and models. 
  2. Selecting appropriate data sets to train the machine learning tools and retrain them whenever necessary.
  3. Determining proper data representation methods.
  4. Analyzing the differences in data distribution that may affect the performance of the tools. 
  5. Conducting research and running tests to improve the performance of machine learning models. 
  6. Building new machine learning libraries. 
  7. Building applications as per the client’s requirements when the models are ready.

Also Read: Four Types of Machine Learning and How to Build a Great Career in Each

What Skills Must a Machine Learning Engineer Have?

machine learningYou will require a combination of soft and technical skills in your pursuit of how to become a machine learning engineer. You will need:

  • A sound understanding of basic mathematics 
  • Knowledge of linear algebra, probability, statistical analysis, and calculus
  • Acquaintance with computer science fundamentals 
  • Basics in data structures and algorithms
  • Knowledge of data modeling, neural networks, and natural language processing (NLP)  
  • Skills in coordination with other engineers and team management
  • Excellent communication skills 

Now that we have discussed the skills required to be a machine learning engineer and also what the role entails, let’s take you through a step-by-step guide on how to become a machine learning engineer. 

How to Become a Machine Learning Engineer?

Machine learning is already an extremely lucrative field with immense scope for the future. If you are considering how to become a machine learning engineer, here is a checklist of things you should do: 

Step 1: Learn to Code with Python

Python is a computer programming language that every aspiring machine learning engineer should pick up. As a high-level, general-purpose language, the syntax used in Python is extremely easy to remember. It is also relatively more straightforward than other computer programming languages since it uses fewer lines of code to accomplish the same tasks. 

Moreover, Python comes with many built-in libraries for artificial intelligence and machine learning, including a modular machine learning library known as PyBrain, which provides easy-to-use algorithms for machine learning tasks. 

Also Read: What is Python Coding & Why its the Ticket to a Great Career

Step 2: Enroll in a Machine Learning Course

For a career in machine learning, you require a strong background in computer programming, data science, and mathematics. Since most jobs you take up will need at least a Bachelor’s degree, it is a good idea to start from there. To stay updated, you might also want to consider machine learning courses offered by Emeritus from the best universities in the world. 

Step 3: Work on Machine Learning Projects

Just academic knowledge is not enough to build a machine learning career. After all, machine learning is a constantly evolving field. So, you will need practical experience through relevant projects. These give you ample opportunities to learn. 

Taking up machine learning projects will also help you better understand machine learning applications and be looked upon favorably by recruiters from top tech companies. Additionally, they will help your CV stand out from the crowd.

Step 4: Connect with Others in the Industry

machine learningNetworking is vital when it comes to machine learning. It is an emerging field with several exciting applications emerging not only from leading businesses but also from universities and research labs worldwide. Connect with industry professionals and students in the field to learn more about the projects they are taking on. 

Joining online communities is also highly beneficial for aspiring machine learning engineers. They can expose you to various new applications of machine learning technology, offer online courses, and host competitions that will help you hone your skills.

Step 5. Ask Someone to Mentor You

A good mentor can go a long way in helping you fast-track your machine learning career. Considering that it is a relatively new and growing field, the resources you can learn and benefit from are limited. Seeking out professionals who already have a career in the space can help you chart your path and avoid the roadblocks they faced in their professional experience. Learning from them can help you grow much faster. Heed their advice to find the most optimum road to success. 

Step 6: Look for Internships

A machine learning internship can put you in direct contact with software engineers and data scientists who are working on the latest machine learning software. This can provide you with valuable practical experience in the field and also help you establish a solid professional network. While personal projects are great, internships will teach you the business-specific skills needed to meet the needs of your future job. 

Is Machine Learning a Good Career?

According to insights from Indeed, machine learning ranks number one in salary and demand. In 2022, the average salary of a machine learning engineer in the US is $146,085. Machine learning is now finding an application in almost every field. As a result, it makes for a great career option. Gaining the relevant skills, qualifications, and certifications in the area will help you outperform the competition, which is bound to arise as demand continues to increase.  

Benefits of an Online Machine Learning Program

Besides degrees, machine learning job aspirants can take up online courses to acquire the necessary skills. Traditional coding degrees don’t always provide the specific skills the bootcamp or short certificate courses will give you. Our need for artificial intelligence and machine learning will continue to rise. With that, the demand for machine learning engineers will also continue increasing. So now that you know how to become a machine learning engineer, are you up for a challenge? This field may just be for you. Start your journey today with an online machine learning course from Emeritus!

By Priya Iyer Vyas

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Content Marketing Manager, Emeritus Blog
Manasa is the content ninja that every brand needs. Apart from being an expert in tech-related trends and digital marketing, she has found her calling in edtech. Her 10-year-long tryst with education started with a teaching fellowship for underprivileged children, followed by a stint as an edupreneur. It gave her the perspective she now uses to create impactful content for Emeritus. Manasa loves the life of a digital nomad that allows her to travel and hopes her reels go viral on the Gram.
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