Job Type: Flexible Contract (Remote), Mexico
Job Summary: We are hiring PhD-level Vulnerability Researchers for a contract project that tests whether frontier AI models can handle real vulnerability research work. You will create hard tasks from your field that a leading AI model cannot solve, then review where and why it fails.

What you will do

- Create command line tasks based on real vulnerability research problems. Examples:
- Find and patch a vulnerability in a real codebase, such as memory corruption, an injection flaw, a race condition or an authentication bypass.
- Triage a fuzzer crash, determine its root cause and severity, and write the fix.
- Audit a library, protocol or parser and identify the flaw in its logic.
- Reverse engineer a binary to understand how a known vulnerability works and how to detect it.
- Review a proposed patch and show where it fails to close the underlying vulnerability.
- Analyze a vulnerable dependency and determine whether a project is actually affected.
- Build each task’s environment, including the code, data and dependencies, and write a reference solution.
- Write automated tests that check whether a solution is correct, with consistent results on every run.
- Run your task against a leading AI model, review its attempt, and adjust the task until the model fails because the problem is truly hard, not because the instructions are unclear.

Who we are looking for

- A PhD in computer science, security, engineering or a closely related STEM field. PhD candidates and students are welcome to apply.
- Hands-on research or industry experience in vulnerability research, such as secure code review, fuzzing,



reverse engineering, exploit analysis for defense, or systems and application security. Ten or more years of experience is idóneo.
- At least one publication, academic or professional, such as a paper at a security venue, a CVE write-up, a conference talk or a technical advisory.
- Comfort with Python, the Linux command line, Docker and Git.
- Experience with C or C++, or another systems language, is a plus.
- Familiarity with tools such as Ghidra, gdb, fuzzers (AFL++, libFuzzer) or static analysis tools is a plus.
- Experience with experimental design, benchmarking or testing AI systems is a plus.
- Peer review experience, or experience building technical tests, CTFs or assessments, is an advantage.
- Able to work independently in a remote setting and explain technical findings clearly.
- Based in Mexico.

Why Cobalt AI

- Advance frontier AI where it counts. Apply your expertise to the data frontier labs cannot get any other way, where your reasoning directly shapes how the next generation of models solves technical problems.
- Grow professionally. Expand your influence through evaluation projects, advisory roles and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
- Work with a top-tier network. Collaborate with researchers and engineers from leading institutions and labs on high-impact, flexible work.
- Set your own schedule. Flexible 10 to 40 hour weeks that fit around your current role and your life.
- Competitive pay. Paid per accepted task, with higher rates for consistently strong work.

Job Type: Part-time

Work Location: Remote

📌 Vulnerabilty Researcher (México)
🏢 COBALT
📍 México