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AI Lab Salary by Location Explorer

Explore ESTIMATED AI lab salary ranges by location, role, and experience level. Compare compensation data from Levels.fyi, Glassdoor, and LinkedIn for ML researchers, engineers, and more.

Data Explorer
Showing — rows ★ Estimates only — see methodology below
AI Lab Role ⇅Location ⇅Base Salary (USD, ESTIMATE) ⇅Total Compensation (USD, ESTIMATE) ⇅Experience Level ⇅Data Source ⇅

Understanding compensation for AI lab roles can feel like navigating a black box. With the AI Lab Salary by Location Explorer, we aim to shed light on how salaries for machine learning researchers, engineers, data scientists, and other AI lab professionals vary across major tech hubs and remote positions. This tool provides ESTIMATED salary ranges based on publicly available compensation data from sources like Levels.fyi, Glassdoor, LinkedIn Talent Insights, and the Bureau of Labor Statistics.

Whether you're a job seeker evaluating offers, a hiring manager benchmarking compensation packages, or simply curious about the financial landscape of AI labs, this AI lab salary by location explorer offers a data-driven starting point. The estimates encompass base salaries and total compensation (including bonuses, stock grants, and other forms of remuneration), tailored to experience levels from mid-level to senior positions.

Compensation in AI labs is highly competitive, with significant variation depending on factors like location, company size, funding stage, and subspecialty. For instance, a senior machine learning researcher in San Francisco may command a higher total compensation than their counterpart in Austin or Toronto, reflecting local cost-of-living adjustments and talent demand. Remote roles, while increasingly common, often align compensation with either a specific office location or a standardized national scale.

Use this AI lab salary by location explorer as a reference to contextualize offers, negotiate compensation, or understand market trends. While we strive for accuracy, these figures are ESTIMATES and cannot account for all variables such as company-specific equity, signing bonuses, or unique benefits packages. For precise figures, always refer to official offer letters or internal HR resources. Explore the table below to compare salaries across roles, locations, and experience levels, and gain insights into the financial dynamics of AI lab careers.

How It Works

The AI Lab Salary by Location Explorer aggregates ESTIMATED compensation data for AI lab roles across different geographic locations and experience levels. Use the filters above to narrow down the dataset by role (e.g., Machine Learning Researcher, Data Scientist), location (e.g., San Francisco, Remote), or experience level (e.g., Mid-Level, Senior).

The table displays two key metrics:

  • Base Salary (USD, ESTIMATE): The fixed annual salary before bonuses, equity, or other forms of compensation.
  • Total Compensation (USD, ESTIMATE): The combined value of base salary, bonuses, equity grants, and other financial benefits, where publicly available data permits.

Click on any column header to sort the table by that metric. For example, sort by Total Compensation to identify the highest-paying locations for a given role.

Methodology Note

All numeric data in this tool is labeled as an ESTIMATE. These figures are derived from publicly available compensation datasets, including:

  • Levels.fyi: Crowdsourced salary data for tech roles, including granular breakdowns of base pay, bonuses, and equity.
  • Glassdoor: Self-reported salary ranges and company reviews.
  • LinkedIn Talent Insights: Aggregated compensation data from job postings and employer-reported figures.
  • Bureau of Labor Statistics (BLS): Government-published wage data for computer and mathematical occupations.

Compensation estimates reflect typical ranges for mid-level to senior roles in well-funded AI labs, startups, and tech companies with dedicated research divisions. Early-career or entry-level salaries are not represented here. Remote roles are typically benchmarked against either a specific office location (e.g., "Remote - SF Bay Area") or a national average.

These estimates do not account for individual negotiation, company-specific equity structures, or non-monetary benefits like healthcare, retirement contributions, or professional development stipends. For precise compensation details, consult offer letters, HR representatives, or internal benchmarking tools.

Frequently Asked Questions

How accurate are the salary estimates in this tool?
The estimates are derived from publicly available data sources like Levels.fyi, Glassdoor, LinkedIn Talent Insights, and the Bureau of Labor Statistics. While we strive for accuracy, these figures are broad ESTIMATES and may not reflect individual offers, company-specific equity, or unique benefits packages. Always refer to official documentation for precise numbers.
Why do salaries vary so much by location?
Salaries in AI labs are influenced by local cost-of-living, talent demand, and competition. For example, roles in San Francisco or New York typically command higher compensation than those in smaller tech hubs or remote positions. Additionally, companies may adjust salaries for remote employees based on their geographic location or a standardized scale.
How are total compensation estimates calculated?
Total compensation estimates include base salary, bonuses, equity grants (where applicable), and other financial benefits. These figures are sourced from platforms that aggregate crowdsourced data (Levels.fyi) or employer-reported compensation (LinkedIn Talent Insights). Equity values are often ESTIMATED based on typical vesting schedules and strike prices for similar roles.
Are remote salaries competitive with in-office roles?
Remote salaries can vary widely. Some companies benchmark remote compensation against a specific office location (e.g., "Remote - SF Bay Area"), while others use a national or global average. Remote roles may offer slightly lower compensation than in-office positions in high-cost areas, reflecting reduced relocation or office overhead costs for employers.
How can I use this tool to negotiate my salary?
Use the salary ranges as a benchmark to understand where your offer falls within the market. If your offer is below the ESTIMATED range for your role, location, and experience level, you can use this data to negotiate for higher compensation. Keep in mind that factors like company size, funding stage, and specific expertise can influence offers.
Does this tool include data for early-career or entry-level roles?
No, this tool focuses on mid-level to senior roles in AI labs, where compensation data is more widely available and standardized. Entry-level salaries often require negotiation and are less frequently reported in public datasets.
Why are some locations missing or not included in the data?
The dataset prioritizes locations with robust public compensation data for AI lab roles. Smaller tech hubs or regions with fewer active AI labs may lack sufficient data for reliable estimates. We encourage users to contribute to crowdsourced platforms like Levels.fyi to improve coverage over time.
How often is the data updated?
The estimates are based on data snapshots from 2022-2023. While AI lab compensation trends evolve gradually, real-time updates are not feasible due to the nature of public data aggregation. For the most current figures, refer to primary sources like Levels.fyi or company-reported data.
Career Resources

Navigate Your AI Lab Career with Confidence

Salaries are just one piece of the puzzle. Explore our general career resources to learn about hiring trends, lab culture, and strategies for thriving in AI research and engineering roles. Whether you're negotiating your next offer or planning a career transition, our guides provide actionable insights to help you succeed.

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