Applied Scientist, AGI

Amazon•Cambridge, MA

16d

About The Position

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences.

Requirements

3+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice To Haves

PhD in computer science, machine learning, engineering, or related fields
Experience or publications related to Agentic AI applications
Programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch
Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
Experience with patents or publications at top-tier peer-reviewed conferences or journals

Responsibilities

Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI
Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results
Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems
Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports