Description
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
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Design benchmark tasks by ideating a vulnerability class (type/subtype + difficulty) and validating the intended exploit behavior
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Create or validate small runnable codebases (“environment/” repos) that include ingestion plus prompt/tool usage where the trust boundary is violated
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Validate the attack via an exploit script and document the unsafe behavior clearly
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Validate implementation of a patch that prevents the exploit and verify the fix is effective
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Produce task metadata (e.g., severity mapping, exact file/line locations, impact analysis, remediation summary, references)
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Conduct review + QC to ensure paths resolve, line ranges are correct, labels aren’t leaked, and the fix blocks the exploit
Ideal Qualifications
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2+ years of experience in software engineering, with a focus on application security, vulnerability research, or secure software engineering
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Degree in Software Engineering, Computer Science, or a related field (Bachelor's minimum; advanced degree preferred)
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Strong proficiency in Python, JavaScript, TypeScript, or other common languages found in open-source projects
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Familiarity with version control workflows (Git, PRs, issue tracking)
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Comfortable articulating technical reasoning in clear, structured writing
Project Timeline
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Start Date: Immediate
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Duration: 1–2 months
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Commitment: Part-time (15–25 hours/week, with flexibility up to 40 hours/week)
Application & Onboarding Process
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Upload your resume
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AI interview: A short, 15-minute conversational session to understand your background, experience, and interest in the role
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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!
Interested in this position?
Apply directly on the company's website