Important points
To begin your career in machine learning, you can start with an entry-level role while gaining skills and experience in the field.
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Machine learning experts may work on projects involving computer vision, bioinformatics, and robotics.
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With a master’s degree and machine learning skills and experience, you can eventually move into advanced machine learning roles, such as machine learning architect or machine learning research scientist.
Explore machine learning career paths to understand what a career trajectory in machine learning looks like. Then, when you’re ready to start building your machine learning skills, consider enrolling in the Machine Learning Specialization. In just two months, you’ll have the opportunity to learn how to build recommender systems using collaborative filtering approaches, build and train neural networks, apply machine learning techniques for clustering and anomaly detection, and more. Once you’re done, you can add this shareable credential to your resume or LinkedIn profile.
What is machine learning?
Machine learning is a type of artificial intelligence (AI) that uses algorithms and other tools to give computers and robots the ability to understand and respond to data. Machine learning allows you to leverage experience and learn from your mistakes, creating computer algorithms that can learn and adapt to different situations. In this way, computers using machine learning explore the world in the same way humans do, analyzing complex environments, leveraging past experience, and learning from mistakes.
machine learning applications
As a Machine Learning Engineer, you can start in an entry-level position and work your way up to leadership roles in a variety of industries and machine learning applications. You can work on projects such as:
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natural language processing: Natural language processing (NLP) is a technology that allows machines to understand and respond to human speech. It uses machine learning and AI to understand language patterns and respond to prompts in ways that mimic human responses.
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Bioinformatics: Bioinformatics is a method of processing, understanding, and deriving meaning from biological data, such as DNA and protein sequences. To work with such large datasets, you need to know the principles and technologies of machine learning.
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Robotics: Machine learning can be used to operate robots. In some cases, technologies such as computer vision and NLP are used to give the robot additional capabilities and provide machine learning to help the robot analyze and understand its environment.
Machine learning career path
You can start your career in machine learning with roles such as junior machine learning engineer, associate data scientist, or junior software engineer. Gaining experience, learning new skills, or earning a higher degree may qualify you for more advanced positions, such as data scientist or machine learning engineer. Later in your career, you may be eligible for more senior roles such as Senior Machine Learning Engineer, Machine Learning Research Scientist, or Machine Learning Architect.
read more: 7 Machine Learning Roles and How to Get Started
Machine learning jobs for beginners
To begin a career in machine learning, you typically need a bachelor’s degree in a field such as computer science, data science, statistics, or engineering. In some cases, you can start your machine learning career without formal education, with certifications that demonstrate your field experience and skills. These roles may support senior or mid-level machine learning professionals.
*All salary information represents the median total salary from Glassdoor as of April 2026. These figures include base salary and additional pay, which may include profit sharing, commissions, bonuses, or other compensation.
Junior Machine Learning Engineer
Median total salary in the US: $146,000 [1]
Employment outlook (growth forecast from 2024 to 2034): 34 percent [2]
As a junior machine learning engineer, you will work with senior engineers to develop and improve machine learning systems. You will support the development, testing, and research of new machine learning techniques and algorithms.
Associate Data Scientist
Median total salary in the US: $140,000 [3]
Employment outlook (growth forecast from 2024 to 2034): 36 percent [2]
As an Associate Data Scientist, you’ll work with teams to analyze data and glean insights from it. In this role, you can help design and create machine learning software or research and test machine learning algorithms.
junior software engineer
Median total salary in the US: $131,000 [4]
Employment outlook (growth forecast from 2024 to 2034): 15 percent [5]
As a Junior Software Engineer, you will work with a team of development experts to develop, test, and integrate software, web projects, and database projects. In this role, you can write code, debug programs, and troubleshoot any issues that arise.
Intermediate role in machine learning
Once you have field experience, a certificate, or an advanced degree, you may be ready to move into a mid-level machine learning role, such as a data scientist or machine learning engineer. Senior roles support strategy and vision direction, entry-level roles support machine learning tasks, while mid-level machine learning professionals drive machine learning implementation.
data scientist
Median total salary in the US: $155,000 [6]
Employment outlook (growth forecast from 2024 to 2034): 34 percent [2]
Data scientists collect, process, analyze, and interpret data to help businesses and organizations gain meaningful insights. Then, demonstrate your findings by providing recommendations and visualizations to stakeholders.
machine learning engineer
Median total salary in the US: $161,000 [7]
Employment outlook (growth forecast from 2024 to 2034): 34 percent [2]
As a Machine Learning Engineer, you will design, build, and implement machine learning models. Train and fine-tune your model using machine learning techniques and evaluate its performance.
Advanced roles in machine learning
Landing a senior machine learning position requires a combination of formal education, skills, and experience working with machine learning. Advanced positions such as senior machine learning engineer, machine learning research scientist, and machine learning architect often require a master’s degree.
Senior Machine Learning Engineer
Median total salary in the US: $213,000 [8]
Employment outlook (growth forecast from 2024 to 2034): 34 percent [2]
As a Senior Machine Learning Engineer, you will lead a staff of machine learning experts and design machine learning models and algorithms. Help drive innovation by introducing new technologies and advancements to your team and setting the overall strategy your team will use.
machine learning researcher
Median total salary in the US: $228,000 [9]
Employment outlook (growth forecast from 2024 to 2034): 20 percent [10]
As a machine learning researcher, you will research, develop, and create new AI systems using the latest technology and scientific methods. In this role, you will lead a team to create machine learning systems that solve real-world problems across a variety of industries.
machine learning architect
Median total salary in the US: $182,000 [11]
Employment outlook (growth forecast from 2024 to 2034): 20 percent [10]
As a machine learning or AI architect, you develop the infrastructure and systems needed for machine learning or AI systems to work, including understanding what a model needs to accomplish, determining which technology is best, and auditing processes to look for improvements.
Is ML a high paying job?
According to Glassdoor, the average total salary for a machine learning engineer is $161,000 [7]. This role pays well compared to the median weekly wage of $1,204, or $62,608 per year, for all other occupations as reported by the U.S. Bureau of Labor Statistics (BLS). [12].
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