About the job
As a Sr. Applied Scientist, you will help solve a variety of technical challenges and mentor other scientists. You will be the thought leader of the team. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people.
Responsibilities
Develop a novel framework and advance the theory and practice of multi-object tracking, re-identification, person activity understanding, multi-modal foundation model, and generic video understanding
Create innovative techniques for efficient visual processing that can scale to real-world applications
Investigate approaches to reduce the computational and data requirements of visual AI systems
Qualifications
Minimum
PhD, or Master's degree and 6+ years of applied research experience
5+ years of building machine learning models for business application experience
Experience with neural deep learning methods and machine learning
Track record of publications at top-tier conferences (CVPR, ICCV, ECCV, NeurIPS, ICLR), specifically focusing on multi-object tracking, re-identification, human activity understanding, or multi-modal LLMs
Strong background in computer vision, deep learning, and multi-modal foundation models
Experience with PyTorch or other deep learning frameworks
Demonstrated ability to transform research ideas into practical implementations
Preferred
Knowledge of modern visual-language models and multi-modal AI systems
Experience with large-scale model training and optimization
Contributions to open-source AI projects or research frameworks
Experience mentoring junior researchers and collaborating with engineering teams
Strong track record of turning research breakthroughs into practical applications