About the job
As a researcher on the Alignment team, you will design and run experiments that improve our ability to oversee increasingly capable models. You will work on hands-on model training, evaluation design, and research infrastructure, and translating promising oversight ideas into systems that can operate on real model traffic and real user workflows. This role combines longer-horizon research with shorter deployment sprints, with projects typically scoped around 3-6 month research timelines and aimed at directly improving future model behavior.
Responsibilities
Design and implement alignment experiments focused on oversight systems for increasingly agentic AI models.
Deploy practical systems for action monitoring, red-teaming, and human-in-the-loop control.
Develop evaluations for alignment failure modes of the frontier models such as overeagerness, instruction following failures, covert actions, avoiding restrictions and scheming propensity.
Analyze deployment data to understand model failures, oversight gaps, and opportunities for training more aligned models.
Develop techniques for feeding oversight signals back into training while preserving the reliability and independence of the oversight process.
Produce externally publishable research when results advance the broader science of alignment.
Collaborate across research, product, security, safety, and engineering teams to turn alignment ideas into working systems.
Move quickly from research intuition to working experiments, prototypes, and evidence that can shape future models.
Qualifications
Minimum
No minimum qualifications listed.
Preferred
Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs.
Have experience with reinforcement learning, post-training, preference optimization, scalable oversight, model evaluation, or adjacent empirical ML research.
Have strong engineering execution and can turn ambiguous research ideas into reliable experiments, tools, training pipelines, and production-facing systems.
Have research intuitions for what experiments are likely to teach us something, while staying grounded in implementation details and empirical results.
Are a team player - willing to do a variety of tasks that move the team forward.
Enjoy fast-paced, collaborative research environments where priorities shift as models and evidence change.
See safety and usefulness as coupled goals.