Machine Learning Career Path: Charting Your Journey in a Dynamic Field

Machine learning is a dynamic and growing field that powers technology like computer vision, natural language processing (NLP), and robotics. To start a career in machine learning, you may start in an entry-level role as you build skills and experience in the field. As your career progresses or you pursue additional credentials like an advanced degree, you may qualify for jobs with more responsibility, leadership, and higher pay. 

Explore a machine learning career path to understand what the trajectory of your career in machine learning might look like. 

What is machine learning?

Machine learning is a type of artificial intelligence (AI) in which you use algorithms and other tools to give a computer or robot the ability to understand and respond to data. You can use machine learning to create a computer algorithm that can learn and adapt to different situations, using experience to learn from mistakes and achieve success. In this way, computers that use machine learning explore the world similarly to humans: analyzing complex environments, drawing on past experiences, and learning from mistakes as they go. 

Machine learning applications

As a machine learning engineer, you can start in an entry-level position and work your way up to a leadership role in many different industries and machine learning applications. You can work on projects like: 

• Computer vision: Computer vision is the ability for computers or robots to analyze and process visual data. It uses machine learning to teach the computer how to understand and respond to the objects found in images and video. 

• Natural language processing: NLP is the technology that allows machines to understand and respond to human speech. It relies on machine learning and AI to understand language patterns and respond to prompts in a manner that replicates the way a human would respond. 

• Bioinformatics: Bioinformatics is a method of processing, understanding, and deriving meaning from biological data like DNA or protein sequences. To work with such a large dataset, you will need to know machine learning principles and technologies. 

• Robotics: You can use machine learning to work with robots. In some cases, you will work with technology like computer vision or NLP to give robots more functionality as well as using machine learning to help the robot analyze and understand the environment. 

Machine learning career path

You can start your machine learning career in roles like junior machine learning engineer, associate data scientist, or junior software engineer. As you gain experience, learn new skills, or pursue a higher degree, you may qualify for more advanced positions like data scientist or machine learning engineer. Later in your career, you may qualify to take on more senior roles like senior machine learning engineer, machine learning research scientist, or machine learning architect. 

Entry-level machine learning jobs

To start a career in machine learning, you will typically need to earn a bachelor’s degree in a field like computer science, data science, statistics, or engineering. In some cases, you may start a machine learning career with experience in the field or certifications that demonstrate your skills without formal education. In these roles, you may provide support to senior or mid-level machine learning professionals. 

Junior machine learning engineer

Average salary in the US (Glassdoor): $116,688 [1]

Job outlook (projected growth from 2023 to 2033): 36 percent [2]

As a junior machine learning engineer, you will work alongside senior engineers to develop and improve machine learning systems. You will help develop, test, and research new machine learning techniques and algorithms. 

Associate data scientist

Average salary in the US (Glassdoor): $109,748 [3]

Job outlook (projected growth from 2023 to 2033): 36 percent [2]

As an associate data scientist, you’ll work with a team to analyze and glean insights from data. In this role, you may help design and create machine learning software or research and test machine learning algorithms. 

Junior software engineer

Average salary in the US (Glassdoor): $108,827 [4]

Job outlook (projected growth from 2023 to 2033): 17 percent [5]

As a junior software engineer, you will work with a team of development professionals to develop, test, and integrate software, web projects, or database projects. In this role, you may write code, debug programs, and troubleshoot problems as they arise. 

Mid-level roles in machine learning 

After you’ve gained experience in the field, certificates, or an advanced degree, you may be ready to move into mid-career machine learning roles like data scientist or machine learning engineer. While senior positions help direct strategy and vision and entry-level roles provide support to machine learning tasks, mid-career machine learning professionals are the drivers of machine learning implementation. 

Data scientist

Average salary in the US (Glassdoor): $118,075 [6]

Job outlook (projected growth from 2023 to 2033): 36 percent [2]

As a data scientist, you will collect, process, analyze, and interpret data to help companies or organizations gain meaningful insights. You will then provide recommendations or visualizations to stakeholders to demonstrate your findings. 

Machine learning engineer

Average salary in the US (Glassdoor): $122,823 [7]

Job outlook (projected growth from 2023 to 2033): 36 percent [2]

As a machine learning engineer, you will design, build, and implement machine learning models. You will use machine learning techniques to train and fine-tune models as well as evaluate model performance. 

Senior roles in machine learning 

To move into senior roles in machine learning, you will need a combination of formal education, skills, and experience working with machine learning. In many cases, you will need a master’s degree to move into senior roles like senior machine learning engineer, machine learning research scientist, or machine learning architect. 

Senior machine learning engineer

Average salary in the US (Glassdoor): $156,550 [8]

Job outlook (projected growth from 2023 to 2033): 36 percent [2]

As a senior machine learning engineer, you will play a leadership role on a staff of machine learning professionals to design machine learning models and algorithms. You will help drive innovation by introducing new technologies and advances to your team and play a role in setting the overall strategies your team uses.

Machine learning research scientist

Average salary in the US (Glassdoor): $153,463 [9]

Job outlook (projected growth from 2023 to 2033): 26 percent [10]

As a machine learning research scientist, you will research, develop, and create new AI systems using the latest technology and the scientific method. In this role, you will lead a team to create machine learning systems that solve real-world problems in many different industries. 

Machine learning architect

Average salary in the US (Glassdoor): $135,237 [11]

Job outlook (projected growth from 2023 to 2033): 26 percent [10]

As a machine learning or AI architect, you will develop the infrastructure and systems needed for a machine learning or AI system to function, such as understanding what the model needs to accomplish, deciding which technology is most appropriate, and auditing your process to look for improvements. 

Prepare for your machine learning career path on Coursera

You may begin your machine learning career path in an entry-level role like a junior machine learning engineer or associate data scientist. With experience and more education, you can move into senior roles like machine learning research scientist or machine learning architect. 

If you want to learn skills to help you take your machine learning career to the next level, consider taking online courses on Coursera. For example, you could learn well-rounded skills with the Machine Learning Specialization offered by Stanford and Deep Learning.AI. You can also learn role-specific skills with a Professional Certificate like the IBM Business Intelligence (BI) Analyst Professional Certificate.