Applied Scientist, Ambient Perception Technology

Found in: Talent US C2 - 2 weeks ago


Sunnyvale, United States Amazon.com Services LLC Full time
The Ambient Perception Technology team under Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for cloud and edge applications.

Key job responsibilities
As an Applied Scientist with the Ambient Perception Technology team under AGI, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of CV technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in within perception domain.

A day in the life
An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice.

About the team
The Ambient Perception Technology team has a mission to deliver best in class CV, Audio and multimodal models in support of various edge and cloud applications.

We are open to hiring candidates to work out of one of the following locations:

Sunnyvale, CA, USA

BASIC QUALIFICATIONS

- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
- 1+ years of building models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms

PREFERRED QUALIFICATIONS

- Have publications at top-tier peer-reviewed conferences or journals
- Experience in Vision Language Models, Audio-Video fusion and multi-modal LLMs
- Experience with optimizing computer vision models for on-device deployment (pruning, quantization, distillation, etc.)
- Effective verbal and written communication skills with non-technical and technical audiences.



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