AI Safety Expert – English, Telugu
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Job Description
AI red-teaming expert probing conversational models for Mercor, which partners with AI labs to train frontier systems. Finding vulnerabilities and producing reproducible safety data.
Responsibilities:
- Red-team conversational AI models and agents through jailbreaks, prompt injections, misuse cases, bias exploitation, and multi-turn manipulation
- Annotate failures, classify vulnerabilities, and flag systemic risks
- Follow taxonomies, benchmarks, and playbooks to keep testing consistent
- Produce reproducible reports, datasets, and attack cases for customers
- Review AI outputs involving sensitive topics such as bias, misinformation, or harmful behaviors
- Uncover vulnerabilities automated tests miss
- Expand evaluation coverage and reduce production surprises
- Strengthen customer AI systems through reproducible adversarial testing
Requirements:
- Native fluency in English and Telugu is required
- Strong judgment about language and content, including assessing whether AI responses are accurate, complete, and appropriate
- Ability to explain reasoning clearly to technical and non-technical audiences
- Rigorous attention to subtle errors, inconsistencies, and gaps
- Ability to work consistently to guidelines and quality standards
- Adaptability across projects, task types, and customers
- Independent contractor engagement
- Must be able to work without access to confidential or proprietary information from any employer, client, or institution
- H1-B and STEM OPT candidates are not supported
Benefits:
- Fully remote role that can be completed on your own schedule
- Weekly payments via Stripe or Wise based on services rendered
- Participation in higher-sensitivity projects is optional
- Clear guidelines and wellness resources for higher-sensitivity content
- Opportunity to build experience in human data-driven AI red teaming
- Direct role in making AI systems more robust, safe, and trustworthy
- Collaboration with leading researchers
- Referral payments of up to $90 for each successful referral, subject to limits
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