OpenAISan Francisco, CADesigns and runs experiments to improve AI model intent alignment, honesty, calibration, and robustness using RL and empirical ML methods. Trains/evaluates large models like LLMs and integrates techniques into production workflows.
Researcher designing and running experiments on chain-of-thought monitorability in frontier LLMs to support scalable oversight and alignment. Requires strong empirical ML expertise with LLMs, deep interest in model behavior/alignment/interpretability, and ability to translate ambiguous questions into concrete experiments.
As a Simulation Researcher/Engineer, you will design and build simulation environments for training general-purpose robot policies. This role involves working with generative models and classical physics simulation, developing differentiable pipelines, and driving asset generation.
As a Research Scientist on the World Models team, you will invent next-generation world model architectures with a focus on controllability and physical consistency, develop controllability mechanisms, and define and own metrics for physical fidelity and action-following.
Senior researcher studies how training choices shape aligned behavior in frontier models, developing synthetic data, evaluation loops, and experiments to ensure durable, robust tendencies like honest reasoning and instruction-following.
Conducts core research on multimodal foundation models for world-simulations, bridging modeling, data, systems, and evaluation. Requires advanced degree in CS/ML, first-principles scaling intuition, and experience with large-scale GPU training.