Member of Technical Staff - Research, Cyber

The role

You will design and build novel AI benchmarks to assess the real-world capabilities and risks of LLMs for cybersecurity. You will conduct research, collaborate with foundation model labs, and implement benchmark designs at scale.

What you will do

• Design and develop novel, high-impact benchmarks that assess challenging real-world capabilities for cybersecurity
• Conduct research to ensure our benchmarks are valid, reliable, and meaningful
• Collaborate with foundation model labs and enterprise security teams to understand evolving evaluation needs
• Analyze model performance across benchmarks and articulate results
• Publish research findings and contribute to the broader security and evaluation research communities
• Work closely with the infrastructure team to implement your benchmark designs at scale
• Stay current with the latest developments in LLM cyber capabilities and evaluation methodologies

Required qualifications

• Ability to clearly communicate complex research ideas to both technical and non-technical audiences
• Experience working in research teams and integrating feedback

Nice to have

• Cybersecurity experience: Hands-on work in security, e.g., as a security engineer, penetration tester, red teamer or vulnerability researcher
• Systems depth: Strong grounding in operating systems, cloud infrastructure and networking
• Interest in benchmarking: Ideally, you've built cyber evals, CTF challenges or security benchmarks before
• AI-forward: You already use LLMs in your security work
• Previously worked as a security engineer at a security company or on an in-house security team, and/or you have experience on an AI or ML team at a security company
• Strong ties to the security community: CTF teams, conference talks, open-source security tools, or research collaborations, published security research, papers or well-read technical write-ups

Benefits

• Highly competitive salary and meaningful ownership
• Relocation and transportation support
• Health/dental insurance coverage
• Lunch and dinner provided
• Free snacks/coffee/drinks
• Unlimited PTO
• $1,500 housing stipend (within one-mile radius)

About the company

The core methodology behind this platform comes from NLP evaluation research conducted at Stanford. The team has prior work experience at NVIDIA, Meta, Microsoft, Palantir and HRT.