About the Role
Join an expert pool supporting AI safety testing projects. You will lead evaluations across security, fairness, and domain-specific safety, helping identify and address risks before AI systems are deployed.
What You'll Do
Design and lead red teaming campaigns to identify attack vectors in high-risk model capabilities.
Develop jailbreak techniques and document them for reproducibility and knowledge sharing.
Test agent systems for prompt injection vulnerabilities involving untrusted inputs.
Probe tool-enabled models, including those with code execution, browsing, or messaging capabilities, for misuse scenarios.
Design bias testing frameworks and assess fairness across demographic groups and languages.
Audit model behavior against written safety policies and report compliance gaps.
Write moderation guidelines, address edge cases, and review the work of other moderators.
Rate findings by severity and recommend fixes.
What We're Looking For
At least five years of experience in security testing, trust and safety, policy, fairness research, adversarial machine learning, or a related domain such as cyber, biological, chemical, or child safety, along with hands-on AI safety testing experience.
Experience designing test plans, threat models, red team plans, or audits that others have carried out.
Experience leading or reviewing testers or moderators.
Hands-on experience testing AI systems for red teaming, jailbreaks, prompt injection, or tool misuse.
Ability to assess finding severity and write clear, actionable remediation recommendations.
Familiarity with tools such as Burp Suite, Garak, or PyRIT, or knowledge of the OWASP LLM Top 10.
Strong written English skills and the ability to work with sensitive content within ethical guidelines.
Compensation & Benefits
Project-based compensation is $75 to $175 per hour, depending on project, field, and experience. Payment is for hours worked.
Location
Fully remote. Projects range from one week to several months.