Our team’s mission is to build a general-purpose agent that can do anything a human can do on a computer. We’re looking for an applied scientist to innovate new methods of collecting human data at scale. This will involve measuring human-agent interactions and building new evaluations of model capabilities. You’ll work alongside world class AI researchers, engineers, and program managers to identify and implement the best processes for scaling data collection and improving our tech for our early customers. This role is highly cross-functional, leveraging skills across machine learning engineering, machine learning research, and social/cognitive science research to advance our foundational agent in a rapidly-evolving technological environment.
Key job responsibilities
- Own the analysis, documentation, and visualization of our human data
- Build and maintain dashboards for cross-functional audiences
- Work closely with data scientists, engineers and researchers to create robust data pipelines and data collection tools
- Work closely with program managers to optimize data collection processes
About the team
Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs).
Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up!
