Exploit Developer - AI Trainer
DataAnnotation
full-remotemidcontractbackendsecurity Arizona, United States 6 days ago via LinkedIn
100,000 - 240,000 USD/annual
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CybersecurityPenetration TestingRed TeamingVulnerability AssessmentMalware AnalysisThreat IntelligenceOffensive SecurityCodebase PatchingDFIRAI Training
About the role
Role Overview
Exploit Developer - AI Trainer at DataAnnotation. You’ll help advance AI systems by validating and improving how they reason about real-world cybersecurity threats and defenses. Work is flexible, remote, and performed on your own computer with a schedule you control.
Responsibilities
- Evaluate AI-generated cybersecurity content for real-world accuracy and validity (e.g., threat analysis, vulnerability assessments, offensive security techniques).
- Design and solve security-focused technical problems used to train AI systems.
- Write clear technical explanations and security-relevant code.
- Provide feedback that directly shapes the next generation of AI security models.
Qualifications
- 2+ years of hands-on cybersecurity experience (e.g., penetration testing, red teaming, incident response, detection engineering, DFIR, malware analysis, threat intelligence, or adjacent fields, including government/military cyber operations).
- Some coding experience; ability to comfortably navigate and patch a codebase.
- English fluency (native or bilingual) with strong writing skills.
- Bachelor’s degree preferred.
Nice-to-haves
- Cybersecurity certifications (e.g., OSCP, CRTO, GREM, GCFA, CEH, or similar).
Contracting Details
- Independent contractor position.
- Hourly pay for projects: $50–$100+ per hour, with bonus rates on some projects.
- Choose projects and working times; work remotely.
- Payment via PayPal.
Eligibility / Location
- Available only to people in the US, Canada, UK, Ireland, Australia, and New Zealand.
About DataAnnotation
DataAnnotation is a platform that connects independent contributors with paid AI training and evaluation tasks. The company focuses on leveraging state-of-the-art AI models to improve system quality through human feedback, including areas like security and technical content evaluation.
Scraped 6/15/2026