Ai Safety Internship information
See salary details
$10.71 - $12.28
8% of jobs
$12.28 - $13.85
11% of jobs
$14.18 is the 25th percentile. Wages below this are outliers.
$13.85 - $15.43
19% of jobs
The median wage is $16.58 / hr.
$15.43 - $17
14% of jobs
$19.92 is the 75th percentile. Wages above this are outliers.
$18.58 - $20.15
13% of jobs
$20.15 - $21.72
6% of jobs
$21.72 - $23.30
8% of jobs
$23.30 - $24.87
5% of jobs
$24.87 - $26.44
3% of jobs
How much do ai safety internship jobs pay per hour?
As of Aug 13, 2026, the average hourly pay for ai safety internship in the United States is $17.87, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $21.15 per hour, depending on experience, location, and employer.
An AI Safety Internship is a temporary position, usually for students or recent graduates, focused on researching and developing methods to ensure artificial intelligence systems are safe, reliable, and aligned with human values. Interns typically work on projects that might include risk assessment, robustness testing, interpretability, or ethical implications of AI technologies. These internships are often offered by universities, research institutes, or tech companies and provide hands-on experience in a rapidly growing field. Participants gain exposure to cutting-edge research and contribute to solving some of the most important challenges in AI development.
As an AI Safety Intern, you can expect to contribute to projects like developing tools for identifying and mitigating risks in machine learning models, performing literature reviews on safety methodologies, and assisting with experiments to test model robustness. You may collaborate with research scientists, engineers, and other interns to brainstorm solutions and analyze results. The work often involves both independent tasks and team-based problem-solving, offering exposure to real-world challenges in ensuring AI systems operate safely and ethically.
To thrive as an AI Safety Intern, you typically need a strong background in computer science, mathematics, or a related field, along with foundational knowledge of machine learning and ethics. Familiarity with programming languages like Python, machine learning frameworks (such as TensorFlow or PyTorch), and experience with relevant research tools are often required. Critical thinking, effective communication, and a proactive learning attitude set standout candidates apart in this rapidly evolving area. These skills and qualities are crucial for contributing to responsible AI development and addressing complex safety challenges in the field.
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