AI jobs are rising rapidly as AI technology transforms numerous industries. Many US organizations spend extensively on AI to obtain a competitive edge, putting AI-related employment in demand.
Demands for AI Jobs in the US
As we know, AI jobs are popular in the United States. Over the past three years, Indeed Hiring Lab reported a fourfold increase in AI job recruitment. According to the McKinsey Global Institute, AI could add $13 trillion to the global economy by 2030, and the US is well-positioned to capture a large share of this value.
Big data, cloud computing, machine learning, and deep learning breakthroughs are driving demand for AI jobs in the US. So, many organizations across several industries are investing extensively in AI to obtain a competitive edge.
AI Jobs Salaries in the US
AI professionals earn more than other professionals due to increased demand. AI engineers earn $112,806 and data scientists $117,345 per year, according to Glassdoor.
However, AI engineers’ salaries depend on the company, region, and experience. Expert AI engineers may earn more. San Francisco, Seattle, New York, and Boston AI engineers make more than those in other cities.
You must be aware that location, company, education, and experience affect AI jobs’ entry-level salaries in the US. Yet, Glassdoor reports that US entry-level AI scientists earn $90,000–$110,000.
Here, San Francisco, Seattle, New York, and Boston pay more than other cities for entry-level AI scientists.
AI scientists’ salaries can also depend on their company’s size and industry. AI scientists at Google, Amazon, and Microsoft make more than those at startups or consulting firms.
Most entry-level AI scientists need a bachelor’s degree in computer science, statistics, mathematics, or a related discipline. Research-focused employment may require a master’s or Ph.D.
Entry-level AI scientist jobs may also evaluate internships, research experience, and coding abilities in addition to formal degrees.
Popular AI jobs in the US
Data scientist: Collecting, cleaning, and analyzing data to construct prediction models.
Machine Learning Engineers create and implement machine learning models to tackle real-world challenges.
AI Engineer: Builds and maintains AI model training and deployment infrastructure.
Research Scientist: This role advances AI.
Business Intelligence Analyst: AI-powered data analysis and business decisions.
AI Product Manager: Leads AI product development and product strategy.
Robotics Engineers use AI and machine learning to build robots.
Engineers who design natural language processing systems interpret and generate human language.
Computer vision engineers create systems that view and interpret the world.
AI Consultant: This profession advises companies on using AI to improve operations and decision-making.
AI Sales Engineer: Shows potential clients and partners AI technology.
AI Ethics Officer: This professional ensures AI technologies’ ethical development and use.
AI Cybersecurity Analyst: This role develops and implements cybersecurity measures for AI systems.
AI Project Manager: Professionals manage AI project development and deployment.
AI Technical Writer: Writes AI system user guides and technical documentation.
These days, new AI technology and methods are emerging rapidly. So, AI scientists and other professionals must stay current to be competitive and grow their professions.