Description
Paid, part-time remote project helping train frontier AI models on cybersecurity workflows. Earn $300 per accepted task with flexible hours designed to fit around a full-time role.
This is a remote, project-based role for cybersecurity professionals with 1+ years of hands-on experience in vulnerability research. You will complete tasks involving generating code repositories with OSS-fuzz-style vulnerabilities and producing correct patches for them. Work is fully asynchronous with no set hours or meetings required, and tasks can be completed on your own schedule during evenings or weekends. Each successfully accepted task pays $50, with potential bonuses for high quality work and specific quantities up to $180 per repository. This is an excellent opportunity to contribute to cutting edge AI model training while earning competitive pay on a flexible, project-by-project basis.
Responsibilities
- Generate code repositories containing OSS-fuzz-style vulnerabilities
- Produce and validate patches for those repositories
- Complete tasks independently within a flexible, async workflow
Required Qualifications
- 1-2+ years of experience in cybersecurity
- Bachelor's degree in Computer Science or related field
- Experience with vulnerability research or security auditing
Preferred Qualifications
- Experience with fuzzing tools or OSS-fuzz style vulnerability research
- Experience writing and patching code in C, C++, or similar low-level languages
- More than 2 years of hands-on security research experience
Why Apply
- Fully remote, work on your own schedule
- $200 referral bonus for bringing in other qualified experts
Details
- Employment type: Contract
- Commitment: 15 hours/week
- Department: Software Engineering
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