Deep Dive: The Top 5 AI Roles
Overview
Our analysis shows a surge in demand for AI and ML specialists, and skill growth in AI related roles is off the charts. This trend is evident in the data, showing a 22% increase in job postings for machine learning engineers year over year. Similarly, solutions architect roles have grown by 33%.
In this section, we have provided snapshots of the top five roles in demand today, based on the number of jobs posted in January and February of 2024. While there is certainly so much more complexity to get into around AI roles and skills, this is meant as a primer to help you understand the key roles many organizations are hiring for, the skills in demand for each and a broad sense of what you can expect as far as salary.
Dig Deeper Into the Top Five AI Roles:
Occupation
Data Scientist
Data scientists use their knowledge of statistics, data analysis, and communication to extract meaning from data. They sift through massive repositories of information to uncover hidden patterns and trends, using these insights to build models and algorithms that can make predictions, solve complex problems, and ultimately, help organizations make better decisions. The role of a data scientist is essential to creating and maintaining ML and AI models.
Average Salary
For tech professionals with the data science skill
Average U.S. Data Scientist Salary Compared to Overall Average U.S. Tech Salary?
Average years of experience
8.5
Distribution of Years of Experience in a Tech Related Field
Top 10 in-demand skills for data scientists
according to how many postings mention them
Occupation
Machine Learning Engineer
A machine learning engineer takes the models and algorithms created by data scientists and converts them into something that can be used for practical applications. Machine learning engineers are coding wizards who build and deploy, operationalizing the model. They also monitor the model's performance and make adjustments to improve their accuracy over time.
Average Salary
For tech professionals with the machine learning skill
Average U.S. Machine Learning Engineer Salary Compared to Overall Average U.S. Tech Salary?
Average years of experience
12.8
Top 10 in-demand skills for Machine Learning Engineers
according to how many postings mention them
Occupation
Software Engineer
A software engineer is the architect and builder of an AI team. They use their programming skills and understanding of computer science principles to design, develop, test and maintain software applications. They can translate ideas and problems into functional code, ensuring the software runs efficiently and meets discussed needs. They collaborate with other engineers, designers and product managers to bring software projects to life, from basic web applications to complex enterprise systems.
Average Salary
For Principle Software Engineers in the U.S.
Average U.S. Principle Software Engineer Salary Compared to Overall Average U.S. Tech Salary?
Average years of experience
17.7
Distribution of Years of Experience in a Tech Related Field
Top 10 in-demand skills for Software Engineers
according to how many postings mention them
Occupation
Data Engineer
A data engineer builds the pipelines and infrastructure that make data accessible and usable for data scientists and other analysts. Data engineers design, construct and maintain the systems that collect, store, transform and analyze vast amounts of data. They use programming skills and knowledge of databases and cloud technologies to ensure the data is clean, organized and readily available for further exploration.
Average Salary
For Data Engineers in the U.S.
Average U.S. Data Engineer Salary Compared to Overall Average U.S. Tech Salary?
Average years of experience
12.9
Distribution of Years of Experience in a Tech Related Field
Top 10 in-demand skills for Data Engineers
according to how many postings mention them
Occupation
Solutions Architect
A solutions architect bridges the gap between business needs and technological solutions. They act as strategic problem-solvers, analyzing business challenges and crafting the technical blueprints to address them. They consider factors like scalability, security and cost-effectiveness when designing solutions and translate complex technical concepts into clear, actionable plans that stakeholders, both business and technical, can understand. In the world of AI, solutions architects often oversee the implementation process of an AI, ensuring the tool is built and deployed smoothly.