How To Become A Machine Learning Engineer


SOURCE: FORBES.COM
SEP 06, 2024

Written By

Sheryl Grey

Education Writer

Brenna Swanston

Reviewed

|Deputy Editor

Published: Sep 6, 2024, 4:00pm

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Key Takeaways

  • Machine learning engineers typically have at least a bachelor’s degree in computer science, computer engineering or a related discipline. Employers may require candidates to have a master’s degree for some positions.
  • If you don’t have a degree, you may still be able to work in machine learning if you take relevant courses and earn certifications, although employers may prefer applicants with a college education.
  • Machine learning engineer jobs are usually not entry-level roles. You need relevant work experience, specialized skills and knowledge of complex subjects to work in this field.

Machine learning is a discipline that falls under the umbrella of artificial intelligence (AI). It has applications in many industries, including healthcare, finance, entertainment, e-commerce, manufacturing and agriculture. Machine learning plays a role in everything from image recognition and chatbots to predictive text and autonomous vehicles.

Engineers in this field design, develop, test and maintain machine learning algorithms and systems. This article explores how to become a machine learning engineer, including the education, skills, experience and certifications you need to pursue the machine learning engineer career path. Read on to learn more about how to advance into a machine learning engineering career.

What Is a Machine Learning Engineer?

Machine learning engineers develop, design, implement and test programs and algorithms. These professionals train programs to identify patterns and make predictions based on data. They then apply these programs and algorithms to real-world situations. Machine learning engineers use programming languages, software frameworks, systems and other tools to improve or create artificial intelligence systems and models.

Machine learning engineers often collaborate with data scientists, computer scientist specialists, data analysts and other technology professionals as they develop and modify programs to run more efficiently and autonomously.

How To Become a Machine Learning Engineer

Below, we outline the steps to become a machine learning engineer.

Acquire an Education

Machine learning engineers need an education that spans complex technical subjects. There is more than one pathway to start a career in machine learning.

Earning a bachelor’s degree in computer engineering, computer science or a similar field is a typical first step for machine learning engineers. Make sure to take courses that cover machine learning, data structures, programming algorithms, statistics and mathematics. With ongoing advancements in the artificial intelligence field, some schools even offer bachelor’s degrees in artificial intelligence or machine learning.

While bachelor’s degrees open up many job opportunities, employers may prefer or require candidates to have master’s degrees. If you have a bachelor’s degree and want to advance into machine learning, you could earn a master’s degree or complete a postgraduate bootcamp to build your skills. Eligibility requirements for postgraduate training options typically include relevant work experience, a bachelor’s degree and knowledge of math and programming.

If you don’t have a degree, you may still be able to become a machine learning engineer: You can acquire relevant knowledge through certificate programs, specialized courses, AI bootcamps or technical certifications. Keep in mind that employers may prefer job candidates who have formal degrees.

Gain Work Experience

Often, machine learning engineer positions are advanced roles, so it’s essential to gain work experience that allows you to apply your skills in real-world environments as you build a strong portfolio. You may do this through internships or by working in relevant entry- or mid-level jobs.

Build Your Knowledge and Skills with Certifications

Technology changes rapidly, so it’s important to continue learning new concepts in the field. Earning certifications validates your skills, keeps your knowledge up to date and helps make you competitive in the job market. We explore popular certifications for machine learning engineers below.

Machine Learning Engineer Salary

According to June 2024 Glassdoor data, the median annual salary for machine learning engineers is around $165,000, which includes base pay and additional pay like bonuses and profit sharing. The total pay range for these professionals is $131,000 to $210,000.

Certifications for Machine Learning Engineers

Professional certifications validate your skills and understanding of machine learning concepts. These credentials can play a vital role in building your career. Popular certifications for machine learning engineers include:

Amazon Web Services (AWS) Certified Machine Learning – Specialty Certification

Earning this certification verifies your skills in developing, training and deploying machine learning models on AWS. You need at least two years of hands-on work experience in the AWS cloud to pursue this certification. The 65-question exam costs $300, and you can access free training and test preparation materials through AWS.

Databricks Certified Machine Learning Professional

Completing this credential signifies that you can use Databricks Machine Learning for advanced machine learning in the production process. The certification exam consists of 60 questions and costs $200. Databricks recommends at least one year of relevant work experience. Databricks provides a learning library with free and paid options for training and exam preparation.

Google Cloud Professional Machine Learning Engineer

This certification validates your ability to build, train, monitor and optimize machine learning models using Google Cloud technologies. The exam includes 50-60 questions and costs $200. Google recommends at least three years of relevant experience, including at least one year of experience using Google Cloud. Google offers courses, webinars and other resources to prepare you for the certification exam.

IBM Certified Data Scientist – Machine Learning Specialist v1

When you earn this credential, you demonstrate your understanding of IBM AI tools and processes. The exam comprises 61 questions and costs $200. IBM recommends you hold relevant work experience before taking this exam. The company provides access to free and paid training and test preparation courses and materials.

Microsoft Certified: Azure AI Fundamentals

This certification validates your knowledge of artificial intelligence (AI) and machine learning principles pertaining to Microsoft Azure services. The exam takes 45 minutes and costs $99 in the United States. Microsoft offers free training and exam preparation materials.

Frequently Asked Questions (FAQs) About How To Become a Machine Learning Engineer

How long does it take to become a machine learning engineer?

What degree do you need to be a machine learning engineer?

Can I become a machine learning engineer without a degree?

What is a machine learning engineer?

What skills does a machine learning engineer need?

What is the salary of a machine learning engineer?

What qualifications do I need to be a machine learning engineer?