About the job
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. Our work leverages large vision language models (VLMs) with reinforcement learning (RL) and world modeling to solve perception, reasoning, and planning to build useful enterprise agents. 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.
Responsibilities
You will lead our efforts to improve the multi-model perception and reasoning abilities of our AI agent in an applied research role. Responsibilities including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.
Qualifications
Minimum
5+ years' experience building machine learning models
PhD or Master's degree in computer science or related field
Proficiency in Python, Java, C++, or related language
Experience with deep learning methods and tools, e.g., PyTorch, JAX
Preferred
Background in scientific research with a proven ability to generate and implement new ideas in machine learning
Experience with post-training of large Vision Language Models (VLMs).
Willingness to step outside typical role boundaries to get things done — every member of technical staff is expected to write code, design experiments, and interpret results
Ability to communicate results and insights to both technical and non-technical audiences, including through presentations and written reports
Ability to think big about the arc of development of AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems
Capacity to mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team