Member of Technical Staff - Cybersecurity Capabilities

About The Role

We're hiring experienced Security / Cybersecurity Engineers to design and build reinforcement learning environments that teach LLMs to reason about and solve real-world cybersecurity problems, such as finding vulnerabilities in production codebases to generating working exploits and patching them safely.

You'll join a small, high-ownership team and contribute directly to the data layer that powers frontier LLM capability in security.

What You Will Do

• Design and build RL environments and reward functions that produce clean, learnable signals for frontier models on offensive and defensive security tasks across diverse programming languages.
• Build environments covering the full vulnerability lifecycle: discovery in source code, exploiting, patching.
• Build environments for reverse engineering tasks across binaries, bytecode, and obfuscated code.
• Construct verifiable reward signals using fuzzers, sanitizers, symbolic execution, static analyzers, exploit-success checks, and patch-correctness validation.
• Collaborate with others to brainstorm and create new ideas and tools to improve the environment building process.

What We are Looking For

• Strong security fundamentals and broad interests across both offensive and defensive work.
• You read advisories, papers, and writeups, understand vulnerabilities deeply, and have the creativity to translate them into RLVR problems.
• Hands-on experience finding, exploiting, or patching real vulnerabilities through CTFs, bug bounty work, security research, red/blue team engagements, or shipped security work in industry.
• Proficiency in Python and systems programming, plus working comfort in at least one low-level language (C, C++, Rust) and one web/application stack.
• Familiarity with security tooling: fuzzers, sanitizers, debuggers, and disassemblers.

Nice to Have

• Published security research, CVEs, or notable bug bounty findings.
• Strong CTF background or competitive results at events like DEF CON CTF, or similar.
• Deep expertise in a specific area: binary exploitation, kernel security, browser/V8 internals, hypervisor security, cryptographic implementation, web application security, or cloud/container security.
• Experience building or contributing to fuzzing infrastructure, vulnerability scanners, or automated program analysis tools.
• Experience with ML for code or security.
• Built complex interactive RL environments, agent harnesses, or sandboxed evaluation infrastructure.

What we offer

• Competitive cash and equity compensation (>90th percentile)
• Ownership and autonomy in a fast moving startup environment
• Opportunity to work with top machine learning engineers
• Health, vision, dental, benefits
• 401K match
• Lunch provided everyday onsite
• Weekly snack orders
• Visa sponsorship & relocation support available

Compensation Range

$180K - $300K