AI Red-Teamer — Adversarial AI Testing

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves building a pod of AI Red-Teamers who probe AI models with adversarial inputs, surface vulnerabilities, and generate the red-team data that makes AI safer for customers. Red-team AI models and agents: jailbreaks, prompt injections, misuse cases, exploits 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 Flex across projects: support different customers, from LLM jailbreaks to socio-technical abuse testing Qualifications Prior red-teaming experience (AI adversarial work, cybersecurity, socio-technical probing), highly recommended; OR Extensive AI background/education that equips you to learn red-teaming fast Curious and adversarial: instinctively push systems to breaking points Structured: use frameworks or benchmarks, not just random hacks Communicative: explain risks clearly to technical and non-technical stakeholders Adaptable: thrive on moving across projects and customers Nice-to-Have Specialties Adversarial ML: jailbreak datasets, prompt injection, RLHF/DPO attacks, model extraction Cybersecurity: penetration testing, exploit development, reverse engineering Socio-technical risk: harassment/disinfo probing, abuse analysis Creative probing: psychology, acting, writing for unconventional adversarial thinking What Success Looks Like Uncover vulnerabilities automated tests miss Deliver reproducible artifacts that strengthen customer AI systems Evaluation coverage expands: more scenarios tested, fewer surprises in production Mercor customers trust the safety of their AI because you’ve already probed it like an adversary Why Join Mercor Build experience in human data-driven AI red-teaming at the frontier of safety Play a direct role in making AI systems more robust, safe, and trustworthy