Adversarial AI Testing
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We are assembling a human data experts who probe AI models with adversarial inputs, surface vulnerabilities, and generate the red team data that makes AI safer for our customers.
This project involves reviewing AI outputs that touch on sensitive topics such as bias, misinformation, or harmful behaviors. All work is text-based, and participation in higher-sensitivity projects is optional and supported by clear guidelines and wellness resources. Before being exposed to any content, the topics will be clearly communicated.
What You’ll Do
Red team conversational AI models and agents: jailbreaks, prompt injections, misuse cases, bias exploitation, multi-turn manipulation
Generate high-quality human data: annotate failures, classify vulnerabilities, and flag systemic risks
Apply structure: follow taxonomies, benchmarks, and playbooks to keep testing consistent
Document reproducibly: produce reports, datasets, and attack cases customers can act on
Who You Are
You bring prior red teaming experience (AI adversarial work, cybersecurity, socio-technical probing)
You’re curious and adversarial: you instinctively push systems to breaking points
You’re structured: you use frameworks or benchmarks, not just random hacks
You’re communicative: you explain risks clearly to technical and non-technical stakeholders
You’re adaptable: thrive on moving across projects and customers
Nice-to-Have Specialties
Socio-technical risk: harassment/disinfo probing, abuse analysis, conversational AI testing
Creative probing: psychology, acting, writing for unconventional adversarial thinking
What Success Looks Like
You uncover vulnerabilities automated tests miss
You deliver reproducible artifacts that strengthen customer AI systems
Mercor customers trust the safety of their AI because you’ve already probed it like an adversary
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