The RBKS AI team at Amazon is seeking Applied Scientists to innovate AI features for Ring and Blink cameras, focusing on the intersection of computer vision, generative AI, and ambient intelligence. The role involves productizing research into advanced computer vision and multimodal GenAI models for video understanding, object detection, and real-time applications, with an emphasis on privacy-preserving, efficient fine-tuning, and on-device/in-cloud inference. The goal is to ship AI solutions that enhance home security for millions of customers.

This role focuses on designing and building machine learning solutions to enhance customer awareness and product discovery for Amazon's Private Brands. It involves end-to-end project management from ideation to launch, utilizing methods like NLP, deep learning, reinforcement learning, and causal inference. The scientist will work closely with engineering and business teams to solve complex problems and drive measurable business impact.

Senior Applied Scientist role focused on developing and productionizing media planning models and solutions for Amazon Ads. The role involves leveraging various ML techniques, including deep learning, generative AI, causal inference, NLP, and computer vision, to provide measurement insights and optimize advertising outcomes. It requires collaboration with engineering, product management, and business teams, and includes mentoring junior scientists and engaging with the scientific community.

This role focuses on developing and implementing innovative media planning and measurement solutions within Amazon Ads. It involves creating end-to-end ML/DL models, from inception to production, to provide insights and recommendations for advertisers. The role requires a strong foundation in ML/DL, experience with productionizing models, and the ability to work with large datasets and collaborate with cross-functional teams.

PhD student internship focused on applying machine learning, NLP, computer vision, automated reasoning, or robotics to solve complex business problems and deploy solutions into production at Amazon.

Software Development Engineer role focused on building and deploying computer vision and machine learning systems for Amazon's global fulfillment network. The role involves end-to-end ownership of systems that provide vision-based insights for item identification, defect detection, and decision-making in manual and robotic operations, supporting downstream business processes and flagship devices.

Applied Scientist role focused on building and refining Generative AI and ML models to optimize Amazon's Ad Sales business. The role involves conceptualizing research, guiding technical approaches, conducting data analysis, running A/B experiments, and working with engineers to deliver end-to-end solutions into production. The goal is to transform account team operations with actionable insights, recommendations, and GenAI integration for improved efficiency.

Applied Scientist role focused on designing and building machine learning solutions for customer discovery of Amazon's Private Brands. The role involves end-to-end project management from ideation to launch, with a strong emphasis on causal ML, deep learning, and deploying models to production. The goal is to drive customer awareness and product discovery, impacting Amazon's own brands and contributing to broader discovery solutions across the company.