Responsibilities

Deep cybersecurity expertise is enough to get started—you do not need prior AI or machine-learning experience. If you know how to investigate vulnerabilities, reason about security failures, and verify that a fix works, we want to hear from you. We will teach you our AI tooling and evaluation workflows.
Build cybersecurity environments. Create isolated, reproducible environments with real repositories, applications, services, logs, and access controls. Make them straightforward to launch, reset, and evaluate at scale.
Turn security work into tasks. Design scenarios around vulnerability discovery and remediation, application and API security, authentication and authorization, incident investigation, and system hardening. Define what the agent knows, which tools it can use, and what it must accomplish.
Develop reference solutions and verifiers. Reproduce the underlying issue, implement a valid solution, and write checks that distinguish a real fix from a superficial workaround. Verify that attacks fail after remediation while legitimate behavior continues to work.
Test the tests. Challenge graders with incomplete fixes, disabled features, hard-coded answers, and other shortcuts. Keep hidden solutions and test data out of the agent's environment, and separate genuine model failures from broken infrastructure.
Run and analyze agents. Evaluate frontier models, inspect their tool calls and code changes, and explain where their security reasoning or execution breaks down. Use those findings to improve task coverage and difficulty.
Contribute to benchmarks and research. Work with researchers and engineers to turn strong environments into evaluation suites and training data. Review other contributors' tasks and help document results for future releases.
Who we are looking for
Practical depth in at least one area of cybersecurity, such as application security, vulnerability research, penetration testing, systems security, cloud security, or incident response. Evidence can come from internships, research, open-source work, bug bounties, CTFs, or independent projects.
The ability to read unfamiliar code, reproduce a security issue, understand its root cause, and implement or assess a fix.
Strong programming skills in Python and at least one language used in the systems you investigate, such as C/C++, Go, Java, JavaScript/TypeScript, or Rust.
Comfort with Linux, Git, containers, debugging, and automated testing.

MTS - Research (Cybersecurity) at Collinear AI · LumiJobs

MTS - Research (Cybersecurity)

Responsibilities

Qualification

Required

Preferred

Company

Collinear AI

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