Cyberattacks cause billions in damages annually — ransomware cripples hospitals, data exfiltration exposes millions. As a Cybersecurity Labeling Expert, you'll be on the front lines of AI safety: reviewing real-world conversations flagged as potentially malicious and determining whether they represent genuine threats. Your judgments directly train the systems that keep AI out of the hands of bad actors.
Analyze flagged AI conversations — ranging from plain text to code-heavy exchanges — and apply your security expertise to assess intent and harm across four domains:
Some conversations may involve POC exploit development; your expertise will determine what crosses the line.
The difference between a security researcher and a threat actor often comes down to context, specificity, and intent — exactly what automated systems struggle to detect. Your ground-truth labels directly improve the classifiers that decide what AI will and won't help with.
You're a strong fit if you've done red team consulting, threat intelligence analysis, vulnerability research, or AI safety labeling where nuanced judgment under ambiguity is routine.
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Mercor partners with leading AI labs and enterprises to train frontier models using human expertise. You will work on projects that focus on training and enhancing AI systems. You will be paid competitively, collaborate with leading researchers, and help shape the next generation of AI systems in your area of expertise.