Amazon Principal Applied Scientist - CV/ML Amazon Robotics 

United States, Washington, Seattle 

749129314

Key qualifications:
* Extensive experience in computer vision, from traditional methods (e.g., SIFT, SURF, optical flow) to modern deep learning architectures
* Profound understanding of advanced vision models such as Vision Transformers (ViTs), MultiMAE, and their applications
* Expertise in generative models, particularly diffusion models and their applications in robotics (e.g., diffusion policy)
* Proven track record in developing scalable ML frameworks for online/offline learning, large language models, prediction systems, and continuous model optimization
* Strong background in 3D vision, including multi-view geometry, SLAM and 3D reconstructionKey job responsibilities
* Set the technical direction for the group, bridging classical computer vision techniques with cutting-edge deep learning approaches
* Drive research and development of advanced perception systems, incorporating the latest advancements in self-supervised and multi-modal learning* Lead the integration of vision-language models and foundation models into perception pipelines
* Develop novel approaches for few-shot learning and domain adaptation in robotic perception
* Advance the state-of-the-art in areas such as 3D scene understanding, object pose estimation, and activity recognition
* Drive ideas to products using a comprehensive toolset including deep learning, active learning, and computer vision (camera selection, camera calibration, instance and semantic segmentation, pose estimation, activity understanding)
* Mentor and guide team members in adopting best practices and staying current with rapid advancements in the fieldA day in the life1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

- 10+ years of scientist or machine learning engineer management experience
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience building state of the art machine learning models or developing algorithms