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AI Hiring Trends by Experience Level

Explore AI hiring trends by experience level with estimates on job postings, growth rates, salaries, and remote work. Benchmark your career or hiring strategy.

Data Explorer
Showing rows ★ Estimates only — see methodology below
Experience Level Job Postings (ESTIMATE) Hiring Growth Rate (ESTIMATE) Salary Range (ESTIMATE) Top Skills Remote Work (%) (ESTIMATE)

The AI talent market is evolving rapidly, with demand shifting across experience levels. This AI Hiring Trends by Experience Level Explorer provides insights into how companies are hiring for AI roles at different career stages, from internships to executive positions. Whether you're an entry-level job seeker, a mid-level professional looking for growth, or a senior leader shaping AI strategy, understanding these trends can help you navigate the market effectively.

Based on ESTIMATED data aggregated from LinkedIn Talent Insights, Glassdoor, Levels.fyi, and Bureau of Labor Statistics (BLS), this tool highlights key metrics such as job postings, hiring growth rates, salary ranges, top skills in demand, and remote work availability. For example, entry-level AI roles (0-2 years of experience) show significant growth in job postings, often emphasizing foundational skills like Python and machine learning. Meanwhile, senior-level positions (6-9 years) command higher salaries but exhibit slower hiring growth, reflecting the specialized expertise required.

Use this explorer to compare hiring trends across experience levels, identify gaps in your skill set, or benchmark your hiring strategy if you're an employer. The ESTIMATES provided are derived from public reports and should be interpreted as directional trends rather than precise figures. For instance, salary ranges reflect broad market data and may vary by location, company size, and industry.

Remote work opportunities also differ significantly across experience levels. While entry-level and internship roles often offer higher remote percentages, executive positions tend to require more in-person collaboration due to strategic responsibilities. These insights can help job seekers target roles that align with their work preferences and career goals.

How It Works

This table allows you to filter AI hiring trends by experience level, salary range, or top skills. Each row represents ESTIMATED data for a specific segment, including job postings, hiring growth rates, salary ranges, and remote work availability. Use the filters at the top to narrow down results based on your interests.

For example, if you're exploring mid-level opportunities, you can filter by "Mid-Level (3-5 years)" to see the most in-demand skills and salary expectations for that group. Similarly, employers can use this data to benchmark their hiring strategies against broader market trends.

Methodology Note

All numeric data in this table is labeled as ESTIMATE and is derived from a combination of public sources, including LinkedIn Talent Insights, Glassdoor, Levels.fyi, and Bureau of Labor Statistics reports. Salary ranges are based on aggregated data and may not reflect precise figures for specific roles or locations. Job postings and hiring growth rates are also approximations, intended to provide directional insights rather than exact counts.

Remote work percentages are calculated based on publicly available reports and may vary depending on company policies and regional trends. The top skills listed are based on common keywords found in job postings and industry reports but are not exhaustive.

Frequently Asked Questions

What does 'hiring growth rate' mean in this tool?
The hiring growth rate represents the ESTIMATED percentage increase in job postings for AI roles at a given experience level over a specified period (typically year-over-year). This metric is derived from LinkedIn Talent Insights and other public sources and provides insight into which experience levels are seeing the most demand.
How accurate are the salary ranges provided?
Salary ranges are ESTIMATES based on aggregated data from Levels.fyi, Glassdoor, and other public reports. They reflect broad market trends and may vary significantly by location, company size, industry, and specific job responsibilities. Always cross-reference with local job postings or salary surveys for precise figures.
Why do executive-level AI roles show lower remote work percentages?
Executive-level AI roles often involve strategic decision-making, team leadership, and cross-functional collaboration, which are more commonly conducted in person. While remote work is growing across all experience levels, executives tend to have fewer fully remote opportunities due to the nature of their responsibilities.
How can job seekers use this tool to identify skill gaps?
Job seekers can compare the top skills listed for their target experience level with their own skill set. For example, if you're a mid-level professional and notice that "AI Ethics" or "AI Model Optimization" are in high demand, you might consider upskilling in those areas to align with market needs.
Can employers use this data to benchmark their hiring strategies?
Yes, employers can use these ESTIMATES to compare their hiring trends with broader market data. For instance, if your company is hiring more senior-level AI talent than the market average, it may indicate a need to balance your workforce with entry or mid-level hires.
Are the job postings counts realistic for all locations?
The job postings counts are ESTIMATED and based on global trends. Actual numbers may vary significantly by region, country, or city. For more localized insights, consider using tools like LinkedIn Talent Insights or regional job boards.
How often is this data updated?
This data is based on public reports and is intended to reflect broader trends rather than real-time updates. For the most current insights, we recommend cross-referencing with sources like LinkedIn, Glassdoor, or industry-specific reports.
What are the limitations of using estimated data?
Estimated data provides a directional view of trends but may not capture unique outliers, such as sudden market shifts, niche roles, or company-specific hiring practices. Always use this data as a benchmark rather than a definitive source.
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