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As artificial intelligence reshapes industries across the United States, the demand for skilled AI professionals is skyrocketing. LinkedIn’s recent report, LinkedIn Jobs on the Rise 2026: The 25 Fastest-Growing Roles in the US, highlights the hottest career opportunities, revealing which roles, skills, and locations are leading the charge. From engineers building AI systems to consultants guiding strategic AI adoption, the report underscores a market hungry for expertise in generative AI, machine learning, and data-driven decision-making.
Key Findings
AI roles dominate LinkedIn’s fastest-growing jobs list, with AI engineers, consultants, and AI/ML researchers leading the top ranks.
AI Engineer (No. 1): AI engineers, also known as machine learning engineers, develop AI models to solve complex, human-like decision-making tasks. Essential skills include LangChain, RAG (Retrieval-Augmented Generation), and PyTorch. Industries in demand include Technology & Internet, IT consulting, and business services, with San Francisco, New York City, and Dallas as prime locations. Most candidates come from software engineering or data science backgrounds, requiring around 3.7 years of experience. Flexible work is possible, with 26% remote and 27% hybrid roles.
AI Consultant and Strategist (No. 2): These professionals help companies adopt AI to streamline operations and reach business goals. Required skills are LLM (Large Language Models), MLOps, and Computer Vision. Key industries mirror those of engineers, with Boston added to the top city list. Prior experience averages 8.2 years, often transitioning from business founders, software engineers, or product managers. Remote work accounts for 30%, hybrid 33%.
Data Annotator (No. 4): Data annotators review and label datasets to train AI models accurately. Skills include SEO copywriting, content marketing, and content production. Industries include tech, staffing, and higher education, with Austin, New York City, and San Francisco leading in job availability. Experience averages 3.5 years, with transitions from content management or data analysis. Remote and hybrid flexibility exists at 27% and 29%, respectively.
AI/ML Researcher (No. 5): Researchers design and test algorithms to enhance AI systems, with skills in PyTorch, Deep Learning, and Computer Vision. Most jobs are in tech, higher education, and research services, concentrated in San Francisco, New York, and Boston. Three years of experience is typical, often transitioning from data science or software engineering. Remote flexibility is limited, with 16% remote and 24% hybrid.
Data Center Technician (No. 17): Technicians manage physical servers and infrastructure, requiring data center management, operations, and cabling skills. Main industries include IT consulting, tech, and staffing. Top cities are Washington D.C., Atlanta, and Columbus, Ohio. Average experience is 3.8 years, with minimal remote work (3.6%) and 32% hybrid.
Other roles on the list include strategic advisors, independent consultants, business founders, venture partners, business development executives, and quantitative researchers, reflecting both technological and entrepreneurial growth. LinkedIn analyzed millions of postings from January 2023 to July 2025, highlighting jobs with strong growth rates and significant posting numbers. The rise of AI roles alongside self-employment and consultancy positions illustrates the growing blend of technical expertise and entrepreneurial flexibility in today’s labor market.
What Undercode Say:
The LinkedIn report illustrates a profound shift in the US job landscape driven by AI. These roles do not merely represent short-term trends—they reflect the structural integration of AI into business operations, R&D, and even content management. AI engineers and consultants are now central to the innovation pipeline, combining technical mastery with strategic thinking. For instance, AI engineers aren’t just coding; they are building systems that can mimic human judgment, requiring proficiency in sophisticated tools like LangChain and PyTorch.
The requirement for prior experience across all these positions highlights the complexity of AI work. AI consultant roles demand over eight years of experience, indicating that companies are prioritizing not just technical skills but the ability to guide organizational transformation. Similarly, data annotators and AI/ML researchers show that even entry-level AI positions require domain knowledge in content, data management, or programming. This signals a broadening of AI’s impact beyond engineering into operational and analytical domains.
Location plays a key role in this growth, with hubs like San Francisco, New York City, Boston, and Austin dominating opportunities. This aligns with historical tech clusters but also reflects the concentration of funding, talent, and research institutions. Interestingly, remote and hybrid flexibility varies significantly—high in consultancy and annotation roles, low in hands-on engineering and data center positions. This uneven flexibility may influence talent migration, with highly skilled professionals seeking a balance between city-based high-pay opportunities and lifestyle preferences.
Industries benefiting most from AI adoption include Technology & Internet, IT consulting, and business services. However, LinkedIn’s inclusion of higher education and research services points to AI’s influence on academic and experimental domains. Roles like AI/ML researcher show that foundational AI work—algorithm development, testing, and innovation—remains critical to sustaining long-term AI applications.
The broader trend toward self-employment and consultancy, highlighted by founders and independent consultants, suggests that AI is not just creating jobs but reshaping employment structures. Professionals are increasingly able to leverage specialized skills to serve multiple organizations, reflecting a shift toward agile, project-based work. Moreover, the growing visibility of AI across non-technical roles—sales, marketing, and content—underscores the interdisciplinary nature of modern AI adoption.
From a career strategy perspective, this data signals that learning AI-related skills is increasingly indispensable. For those aiming to enter AI fields, understanding both the technical stack and business applications can provide a competitive edge. Additionally, organizations hiring AI talent must consider hybrid models and upskilling programs to attract and retain qualified personnel.
Ultimately, the LinkedIn findings point to AI as a driver of both specialization and adaptability. As machine learning, generative AI, and data analytics continue to advance, roles that blend technical, strategic, and operational skills will dominate the labor market. AI is no longer a niche field—it is now an essential part of the US workforce ecosystem, influencing career growth, city economies, and the broader professional landscape.
Fact Checker Results:
✅ AI engineer, AI consultant, and AI/ML researcher are among the fastest-growing jobs in the US.
✅ Top locations include San Francisco, New York City, Boston, and Austin.
❌ Remote work is not universally available; some roles, like data center technician, remain office-centric.
Prediction:
📊 AI-related roles will continue to surge, especially in consultancy, engineering, and research, with salaries and remote flexibility rising in tandem.
📊 Non-technical professionals adopting AI literacy will see career acceleration, driving interdisciplinary demand.
📊 Self-employment and hybrid AI projects will expand, creating a gig-like ecosystem for specialized talent.
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References:
Reported By: www.zdnet.com
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