Member of Technical Staff - Cybersecurity Capabilities

About the Company

Preference Model is building automated ML research engineering. The founding team has previous experience on Anthropic’s data team building data infrastructure and datasets behind Claude. We are partnering with leading AI labs to push AI closer to achieving its transformative potential.

Responsibilities

• Design and build RL environments and reward functions that produce clean, learnable signals for frontier models on offensive and defensive security tasks
• Build environments covering the full vulnerability lifecycle: discovery in source code, exploiting, and 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

Requirements

• Strong security fundamentals across both offensive and defensive work
• Hands-on experience finding, exploiting, or patching real vulnerabilities (CTFs, bug bounty, security research, or industry work)
• Proficiency in Python and systems programming
• Working comfort in at least one low-level language (C, C++, Rust) and one web/application stack
• Familiarity with security tooling such as fuzzers, sanitizers, debuggers, and disassemblers
• Problem solvers who take ownership and drive solutions end-to-end

Preferred Qualifications

• Published security research, CVEs, or notable bug bounty findings
• Strong CTF background or competitive results
• Deep expertise in binary exploitation, kernel security, browser/V8 internals, hypervisor security, or cloud/container security
• Experience building fuzzing infrastructure or automated program analysis tools
• Experience with ML for code or security
• Experience building complex interactive RL environments or sandboxed evaluation infrastructure

Benefits

• Competitive cash and equity compensation
• Ownership and autonomy in a fast moving startup environment
• Opportunity to work with top machine learning engineers
• Health, vision, and dental benefits
• 401K match
• Daily onsite lunch and weekly snacks
• Visa sponsorship and relocation support available