Sr Principal Security Researcher – AI (Cybersecurity LLM Post-Training, Evals, and Environments)

What you'll do

• Create cybersecurity datasets, reproducible training and evaluation environments, and verifiable tasks for LLMs and agents.
• Develop graders and evaluations, analyze failures and regressions, and conduct controlled experiments.
• Apply post-training methods and collaborate to bring research into production capabilities.

What they ask for

• Hands-on experience in one or more cybersecurity areas.
• Practical experience developing or evaluating LLM-based systems for cybersecurity, source code, software engineering, or tool-using agents.
• Experience designing datasets, benchmarks, graders, evaluation frameworks, or tasks with verifiable outcomes, and with at least one post-training or model-adaptation method.
• Strong programming skills in Python and at least one of C, C++, Rust, Java, or Go; experience with large codebases, security tools, testing frameworks, build systems, debuggers, and containerized environments.

Nice to have

• Experience building reinforcement-learning environments, cybersecurity agents, coding agents, or other tool-using AI systems.
• Experience with DPO, RLHF, RLAIF, reinforcement learning, process supervision, or model distillation.

Pay

$163,200.00 - $264,000.00/yr (base salary; annual range; currency not stated)

Tools

Python, C, C++, Rust, Java, Go

AI focus

LLM post-training, cybersecurity evaluation, autonomous security agents, dataset and environment development, and model improvement using supervised fine-tuning, preference optimization, reinforcement learning, reward modeling, rejection sampling, and distillation.