AI Safety Red Teamer
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Job Description
AI Safety Red Teamer stress-testing frontier AI models through adversarial prompts. Identifying vulnerabilities and improving model alignment, robustness, and safety for Mercor’s AI lab partners.
Responsibilities:
- Design adversarial prompts to stress-test frontier AI models
- Identify jailbreaks, unsafe behaviours, hallucinations, and policy failures
- Evaluate model robustness across misinformation, cyber, biosecurity, fraud, political content, and other sensitive domains
- Document vulnerabilities and contribute to safety benchmarking and red-teaming reports
- Collaborate with AI researchers to improve model alignment, robustness, and safety
- Work on projects focused on training and enhancing AI systems
Requirements:
- Bachelor's degree or higher in Computer Science, Cybersecurity, Journalism, Communications, Psychology, Biology, Chemistry, Public Policy, or a related discipline
- 5+ years of professional experience in AI Safety, AI Red Teaming, Trust & Safety, cybersecurity, investigative journalism, life sciences, or a related field
- Strong analytical reasoning, prompt design, and written communication skills
- Experience designing adversarial prompts or evaluating frontier AI systems
- Experience with AI Red Teaming, RLHF, SFT, AI Alignment, or Trust & Safety preferred
- Familiarity with jailbreak testing, prompt engineering, or adversarial evaluation methodologies preferred
- Expertise in grey-area domains such as cyber, biosecurity, political content, misinformation, or scientific safety preferred
- Must be able to work as an independent contractor
- H1-B and STEM OPT candidates are not supported
Benefits:
- Fully remote role
- Work on your own schedule
- Weekly payments via Stripe or Wise
- Projects may be extended, shortened, or concluded early depending on needs and performance
- Opportunity to work alongside leading AI researchers and safety teams
- Opportunity to influence frontier AI safety
- Reasonable accommodations available upon request
- Referral payments of up to $340 per successful referral (referral limits apply)
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