Security Researcher Job at Code Red Partners, Santa Clara, CA

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  • Code Red Partners
  • Santa Clara, CA

Job Description

Join an early-stage startup that’s building at the frontier of AI and cybersecurity.

They’re on a mission to design autonomous security systems capable of detecting, triaging, and remediating software vulnerabilities, all without human intervention!

This is a greenfield opportunity to help shape the foundational logic of their product’s vulnerability discovery engine. You’d be working shoulder-to-shoulder with a world-class AI team to push the boundaries of what "self-healing software" can look like.

Key Responsibilities

  • AI-Driven Security Research : Partner with AI engineers to design and build intelligent systems that autonomously detect code vulnerabilities. Leverage large language models (LLMs), industry-leading security tools, supervised fine-tuning, and reinforcement learning to uncover novel security flaws.
  • Vulnerability Triage and Analysis : Investigate and validate identified vulnerabilities to assess severity, exploitability, and potential impact.
  • Responsible Disclosure : Work with impacted organizations to report vulnerabilities responsibly, adhering to established timelines and industry disclosure standards.

Required Qualifications

  • Proven expertise in cybersecurity research and vulnerability analysis.
  • Proficient with static and dynamic code analysis techniques and tools.
  • Hands-on experience in penetration testing or red teaming.
  • Familiarity with machine learning principles and their security applications.
  • Strong communication skills for documenting findings and engaging stakeholders.
  • Practical experience managing responsible disclosure workflows.

Preferred Qualifications

  • Programming skills in Python, C/C++, or similar languages.
  • Active participation in bug bounty programs or security challenges.
  • Track record of published security research, CVE contributions, or speaking at security conferences.
  • Deep understanding of secure coding practices across various programming languages.

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