As part of the AWS Applied AI Solutions organization, we're advancing the frontier of visual reasoning and agentic AI technologies. Our vision is to develop sophisticated AI systems that can understand, interpret, and reason about visual information at human-like levels, enabling breakthrough applications across multiple industries.
Key job responsibilities
- Spearhead research in Agentic AI for complex visual AI challenges
- Innovate novel approaches to efficient visual processing mechanisms for large-scale, real-world applications
- Pioneer advancements in autonomous decision-making and visual reasoning systems, pushing the boundaries of computational and data efficiency
- Define and pursue long-term, high-impact research directions that shape the future of visual AI technologies
- Provide scientific mentorship to junior researchers, fostering a culture of innovation and rigorous research methodology
- Collaborate with cross-functional teams to bridge research with practical applications, influencing the broader scientific community
A day in the life
As a Principal Research Scientist, you'll drive research in visual reasoning and generative AI, defining novel research directions while ensuring impact through practical applications. Your day-to-day work will involve developing theoretical frameworks, conducting deep technical investigations, and validating complex hypotheses through rigorous experimentation. You'll mentor junior scientists in research methodology and experimental design while collaborating with cross-functional teams to translate research insights into scalable solutions.
Your expertise and guidance will be instrumental in shaping both the technical direction of our visual AI initiatives and the development of junior research talent on the team.
About the team
Our research team is tackling fundamental challenges in visual reasoning that combine generative AI and agentic frameworks. We're investigating novel approaches to how AI systems understand spatial relationships, reason about object interactions, and maintain contextual awareness across time. Working at the intersection of computer vision and large language models, we're developing theoretical frameworks and practical techniques that advance the state-of-the-art in visual AI.
- 10+ years of tech industry or equivalent experience
- PhD in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field
- Experience working effectively with science, data processing, and software engineering teams- Experience implementing models and tools through the use of high-level modeling languages (AMPL, Mosel, R, Matlab, Julia)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $170,500/year in our lowest geographic market up to $294,700/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit
https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
