What Is a Machine Learning Engineer? Roles, Skills, and Career Guide

Artificial intelligence is no longer a futuristic technology – it is a core driver of business innovation throughout the United States (US).

As such, machine learning (ML) engineers are in high demand across North America. This is evident from their salaries, which range from USD 113,865 to USD 312,005 annually, with an average of USD 188,485.

They are among the most sought-after professionals as they help organizations build intelligent systems that power everything. 

In this blog, we will explore what a machine learning engineer is and explore different facets of their work. We will also look at the key skills and tools for these professionals, as well as the career paths and opportunities available to them.  

Source: Indeed, as of June 9, 2026

What Is an ML Engineer and What Do They Actually Do in the US?

Let us take a closer look at what machine learning engineers are and what they actually do in the US in 2026. 

1. Definition of an ML Engineer

To  understand what a machine learning engineer is, it is important to first define the role. These are specialized technology professionals who research, design, build, and maintain artificial intelligence systems that run by themselves.  

Their core responsibilities include designing ML systems, training and evaluating models, deploying and scaling solutions, and monitoring and optimizing performance. 

Also Read: What Does a Machine Learning Engineer Do? Roles Explained

2. What Does an ML Engineer Do?

If you want a proper machine learning engineer career guide, you should have a clear idea of what they do:

1.2.1 Data Processing and Pipeline Engineering

They ingest large volumes of data from sources such as databases, web scraping tools, and sensors. 

3. Difference Between ML Engineers and Data Scientists

In this regard, you must know the differences between machine learning engineer roles and data scientist roles. 

The fundamental difference between them is in their respective goals. Data scientists emphasize discovering patterns and mining business insights, and ML engineers prioritize writing software to deploy automated models into production.

Key Skills and Tools for Machine Learning Engineers

The following are the most important machine learning engineer skills and tools in the US in 2026:

​

Also Read: Machine Learning Engineer Salary in the USA: 2026 Outlook

Career Path and Opportunities in the US

We have already discussed what a machine learning engineer is in some detail. We will now look at the career paths and opportunities available to these professionals in the US in 2026.   

1. Salary Outlook

ML engineers are among the highest earners in the tech sector because their supply is around a third of the demand for such professionals. Apart from their salaries, these professionals receive bonuses and company stock, which further add to their annual earnings. 

Experience is the primary driver of baseline salary differentiation. Right now, mid-level talent is experiencing the maximum yearly growth rate.  

2. Industries Hiring ML Engineers

The following table shows the leading industries hiring ML engineers and the most active recruiters therein:

Technology and Frontier AI Labs

This sector is the biggest employer of ML engineers, but that should not come as a surprise to you since you already know what a machine learning engineer is.  

Also Read: Tools Every Machine Learning Engineer Should Know

Build Future-Ready Tech Skills with upGrad US

In 2026, upGrad can be one of your best avenues to build future-ready tech skills in the US: 

• Executive Post Graduate Program in Applied AI and Agentic AI, Indian Institute of Information Technology (IIIT) Bangalore 
• Executive Post Graduate Certificate in Generative AI and Agentic AI, Indian Institute of Technology (IIT) Kharagpur
• Summer Career Accelerator Program, Golden Gate University 
• Master of Science in ML and AI, Liverpool John Moores University  
• Executive Diploma in ML and AI, IIIT Bangalore

FAQs On What Is a Machine Learning Engineer