Work with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission. Conduct research and publish high quality work. Design and execute large-scale experiments, writing high-quality, reusable code, and contributing to a production-ready system using frameworks such as JAX. Learn and understand research in machine learning algorithms. Understand how to use research to drive design decisions.
Design and conduct user studies (e.g. interviews, surveys, controlled experiments, and field deployments) to understand how people interact with, oversee, and provide feedback to AI agents. Prototype novel interfaces and interaction techniques that help people steer, supervise, and collaborate with increasingly autonomous agents. Develop human-centered evaluation methods and metrics for the helpfulness, trustworthiness, safety, and alignment of agents.
Translate insights from human studies into improvements in how agents learn from human feedback and improve themselves (e.g. reward modeling, preference elicitation, and human-in-the-loop reinforcement learning).
Job description provided by Google.
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