AI Lab Salary by Role Explorer
Explore estimated AI lab salary ranges by role with this interactive tool. Compare compensation for Research Scientists, ML Engineers, and more using public data.
| Role | Level | Base Salary (ESTIMATE) | Total Compensation (ESTIMATE) | Equity Value (ESTIMATE) | Source Count | Location Factor |
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Understanding compensation benchmarks is critical for both job seekers and hiring managers in the fast-moving AI industry. The AI Lab Salary by Role Explorer provides an interactive comparison of estimated salaries across different roles within leading AI labs, based on publicly available compensation data from sources like Levels.fyi, Glassdoor, LinkedIn Talent Insights, and the Bureau of Labor Statistics.
AI lab roles vary significantly in responsibilities, required experience, and compensation packages. For example, a Research Scientist (L4) in a top AI lab typically earns an estimated base salary of $180K–$200K, with total compensation (including equity and bonuses) ranging from $250K–$300K. In contrast, Machine Learning Engineers at the same level may see slightly higher total compensation due to differing equity structures. Meanwhile, AI Product Managers or Technical Program Managers often command total compensation estimates between $250K–$350K at mid-level roles, reflecting the strategic importance of cross-functional leadership in AI product development.
This tool allows you to filter by role, experience level, and location adjustment (using a multiplier based on cost-of-living differences). All numbers shown are ESTIMATES and should be interpreted as broad benchmarks rather than precise figures. Compensation can vary widely based on company, geographic region, individual negotiation, and market conditions. Publicly available data from platforms like Levels.fyi suggests that top AI labs (e.g., those in Silicon Valley) tend to offer higher equity components, especially for research-focused roles, compared to industry averages in other tech sectors.
The ai lab salary by role explorer is designed to help researchers, engineers, and hiring professionals make informed decisions about career growth, job offers, and compensation strategies. Whether you're evaluating an entry-level position or a senior leadership role, this tool provides a data-driven starting point for understanding compensation trends in the AI industry.
How It Works
This interactive table aggregates publicly available compensation data from multiple sources, including Levels.fyi, Glassdoor, LinkedIn Talent Insights, and the Bureau of Labor Statistics. The tool allows you to filter by role, level, and location adjustment to see estimated salary ranges for different positions in AI labs. All values are adjusted to a San Francisco baseline (1.0x) for comparability, with other locations scaled accordingly.
Use the filters to explore compensation estimates for specific roles. For example, selecting Research Scientist and L4 will display estimated compensation for mid-level research scientists. The location adjustment filter lets you account for cost-of-living differences, such as comparing San Francisco salaries to those in Austin or remote positions.
Methodology Note
All data in this tool are ESTIMATES and should be treated as directional benchmarks rather than precise figures. Compensation varies based on individual negotiation, company policies, market conditions, and other factors. The estimates are derived from:
- Levels.fyi: Aggregated crowdsourced compensation data from tech professionals, weighted toward top-tier companies.
- Glassdoor and LinkedIn Talent Insights: Self-reported salary ranges, adjusted for outliers and sample size.
- Bureau of Labor Statistics: Broader industry averages for calibration, though AI lab roles may differ significantly from general tech sector trends.
The equity estimates are particularly sensitive to company-specific valuation cycles and should be interpreted with caution. For roles with fewer than 20 data points, estimates are extrapolated from comparable positions and marked as lower-confidence benchmarks.
Frequently Asked Questions
These estimates are based on aggregated public data from sources like Levels.fyi, Glassdoor, and LinkedIn Talent Insights. While we’ve standardized the numbers using San Francisco as a baseline, actual compensation can vary widely depending on the company, negotiation, location, and other factors. Treat these as directional benchmarks rather than precise figures.
Salaries in AI labs vary based on role demand, required expertise, and market conditions. For example, Research Scientists often command higher equity packages due to their direct impact on model development, while Product Managers may see higher bonuses tied to product success. Technical roles (e.g., ML Engineers or AI Infra Engineers) tend to have higher base salaries due to specialized skills.
The tool uses a location factor to adjust estimates based on cost-of-living differences. For instance, salaries in San Francisco are typically 1.0x (baseline), while Austin or Boston may be 0.7x–0.8x. Remote roles may offer lower compensation but include flexibility benefits. The adjustment is applied proportionally to base salary, equity, and bonuses.
Base salary is the fixed annual pay, while total compensation includes bonuses, equity (stock options or RSUs), and other incentives. In AI labs, equity can make up a significant portion of total compensation, especially at senior levels. For example, an L5 Research Scientist may have a base salary of $220K but a total compensation of $350K due to equity vesting.
The data leans toward established AI labs (e.g., top-tier companies with well-documented compensation structures). Startups may offer lower base salaries but higher equity potential, depending on funding and growth trajectory. This tool focuses on roles with sufficient public data, so startup compensation may not be fully captured.
Use this tool to benchmark market ranges for your role and level. For example, if you’re offered $200K for an L4 Research Scientist role in San Francisco, you can compare it to the estimated range of $180K–$250K (total compensation). Keep in mind that equity, benefits, and job-specific factors (e.g., impact of the role) also play a role in negotiations.
This tool focuses on roles with sufficient public data. Niche or emerging roles (e.g., AI Hardware Engineers or AI Ethics Researchers) may have fewer data points, leading to broader estimate ranges. If a role isn’t listed, check back later as we update the tool with new data.
For deeper dives, explore Levels.fyi (tech-focused), Glassdoor (company-specific), or Bureau of Labor Statistics (broader industry trends). This tool synthesizes those sources into a unified view for AI lab roles.
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