SWE (Cybersecurity)

Mercor is hiring experienced Software Engineers specialized in Cybersecurity to support high-impact research collaborations with leading AI labs. Freelancers will contribute to building training datasets that improve AI model reasoning and problem-solving on real-world coding tasks. This is a unique opportunity to apply your software engineering expertise toward shaping the next generation of intelligent systems. About the Project You'll annotate frontier-model trajectories on SWE-bench–style tasks derived from real open-source repositories. Currently, closed-source models do not expose their internal reasoning traces, making it difficult to understand how LLMs approach problem-solving. To address this gap, you'll reconstruct and annotate the reasoning portions of model trajectories—using your own problem-solving process and the full task context to infer and infill the underlying thought process at each step. Key Responsibilities Design benchmark tasks by ideating a vulnerability class (type/subtype + difficulty) and validating the intended exploit behavior Create or validate small runnable codebases (“environment/” repos) that include ingestion plus prompt/tool usage where the trust boundary is violated Validate the attack via an exploit script and document the unsafe behavior clearly Validate implementation of a patch that prevents the exploit and verify the fix is effective Produce task metadata (e.g., severity mapping, exact file/line locations, impact analysis, remediation summary, references) Conduct review + QC to ensure paths resolve, line ranges are correct, labels aren’t leaked, and the fix blocks the exploit Ideal Qualifications 2+ years of experience in software engineering, with a focus on application security, vulnerability research, or secure software engineering Degree in Software Engineering, Computer Science, or a related field (Bachelor's minimum; advanced degree preferred) Strong proficiency in Python, JavaScript, TypeScript, or other common languages found in open-source projects Familiarity with version control workflows (Git, PRs, issue tracking) Comfortable articulating technical reasoning in clear, structured writing Project Timeline Start Date: Immediate Duration: 1–2 months Commitment: Part-time (15–25 hours/week, with flexibility up to 40 hours/week) Application & Onboarding Process Upload your resume AI interview: A short, 15-minute conversational session to understand your background, experience, and interest in the role Follow-up communication within a few days with next steps and onboarding details Apply today and leverage your software engineering expertise to help build the future of AI-driven systems!