AI Jobs in the United States

U.S. AI job market and trends

The AI job market in the United States is growing across industries: technology, finance, healthcare, automotive, retail, and government. Major tech hubs — San Francisco, New York, Boston, Seattle, and Austin host high concentrations of AI research and engineering roles, while companies nationwide are embedding AI into products and operations. Key trends include a shift from pure research to applied ML/AI for production systems, rising demand for MLOps and AI infrastructure skills, and an increase in hybrid and remote roles that expand opportunities beyond traditional tech centers. Salaries remain strong: entry-level roles often start around $90k–$120k, mid-level engineers can earn $130k–$180k, and senior or specialized positions (e.g., research scientist, senior ML engineer) commonly exceed $200k, especially with equity at startups or compensation at FAANG firms. New York, in particular, has a strong presence of AI roles in finance, advertising tech, and media, offering unique cross-disciplinary positions that combine domain expertise with machine learning.

Top AI roles, required skills, and compensation

Common AI positions include Machine Learning Engineer, Data Scientist, Research Scientist, MLOps Engineer, AI Product Manager, and AI Ethics/Policy Specialist. Core technical skills employers look for are: strong programming (Python), ML frameworks (TensorFlow, PyTorch), data engineering (SQL, Spark), model deployment (Docker, Kubernetes), and evaluation/experiment design. Soft skills — communication, domain knowledge, and product thinking — differentiate candidates for applied roles. Education ranges from bootcamp certificates and online courses up to PhDs for research-heavy jobs; many employers value demonstrable project experience as much as formal degrees. Compensation varies by role and location: machine learning engineers in major metros (San Francisco,