Research Scientist focused on large language models and diffusion architectures, developing post‑training techniques and deploying innovations into production.
As a Sr Principal AI Researcher, you will advance the cybersecurity capabilities of large language models and autonomous AI agents by combining security research, rigorous evaluation, and applied LLM post-training.
Compensation
$163,200.00 - $264,000.00/yr
Responsibilities
Design reproducible training and evaluation environments for complex cybersecurity tasks, including vulnerability research, threat analysis, detection, investigation, remediation, secure coding, and autonomous security workflows.
Transform source-code repositories, vulnerabilities, security incidents, malware samples, threat intelligence, detection logic, patches, test harnesses, and security tools into structured tasks for LLMs and AI agents.
Develop high-quality security datasets, including synthetic data, hard negatives, adversarial examples, expert annotations, and model-generated trajectories.
Build reliable graders, verifiers, and reward signals using tests, compilation, runtime behavior, security-tool outputs, detection results, vulnerability reproduction, and other domain-specific validation methods.
Design evaluations for security reasoning, code understanding, threat analysis, root-cause analysis, tool use, long-horizon execution, and autonomous task completion.
Design and execute white-box attacks against advanced AI models, checkpoints, post-training systems, reward functions, data pipelines and evaluation environments.
Locations (2)
Redmond, Washington, United States
United States
Compensation
Research Sciences IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Responsibilities
Design and execute white-box attacks against advanced AI models, checkpoints, post-training systems, reward functions, data pipelines and evaluation environments.
Investigate adversarial behavior including jailbreaks, harmful permissiveness, reward hacking, deceptive behavior, capability elicitation, privacy leakage, data poisoning and model supply-chain compromise.
Build high-fidelity experiments and automated attack suites that reproduce realistic threats and run continuously against new checkpoints and system configurations.
Lead the design, development, and delivery of data products for trust & safety in AI, including RL environments, safety traps, and evaluation metrics for frontier labs.
Compensation
The expected salary range for this position is $180,000 – $220,000 USD per year, based on experience, skills, and qualifications.
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