Applied Scientist III, AGI IMAX Science

Are you an inventive curious and driven Applied Scientist with a strong background in AI Computer Vision and Deep Learning Join Amazons AGI IMAX Science team and contribute to significant advancements in Computer Vision Multimodal Understanding Generative AI and foundational models.

As part of the AGI IMAX Science team youll lead innovative research projects and train large-scale Vision-Language Models (VLMs) diffusion models and multimodal foundation models that directly impact millions of Amazon and AWS customers. Leveraging Amazons vast computing power youll work alongside a supportive and diverse group of skilled scientists and engineers building models and services that make a meaningful difference in the industry.


Key job responsibilities
Lead research initiatives in Computer Vision and Multimodal generative AI advancing model efficiency accuracy and scalability.
Train and fine-tune large-scale Vision-Language Models (VLMs) diffusion models and multimodal foundation models at scale.
Design implement and evaluate deep learning models in a production environment.
Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services.
Publish in top-tier conferences and journals keeping Amazon at the forefront of innovation.
Mentor and guide other scientists and engineers fostering a culture of scientific curiosity and excellence.

- PhD or Masters degree and 4 years of CS CE ML or related field experience
- 3 years of building models for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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

- Experience using Unix/Linux
- Experience in professional software development

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Required Experience:

IC

Employment Type : Full-Time
Experience: years
Vacancy: 1