Applied Science Manager, GenAI, Trust and Store Integrity Science

Description

• The TSI Science team seeks an experienced Applied Science Manager with deep expertise in deep learning and generative AI to lead the development of cutting-edge multi-modal systems. You will manage a team

Description

• The TSI Science team seeks an experienced Applied Science Manager with deep expertise in deep learning and generative AI to lead the development of cutting-edge multi-modal systems. You will manage a team of applied scientists and set the technical direction for building agentic systems that transform multimedia content understanding. This role offers a unique opportunity to create products impacting thousands of professionals while driving operational efficiency at scale. You'll shape Amazon's intelligent platform that converts multi-modal digital evidence—including images, documents, video, audio, and biometrics—into structured data and actionable insights. The platform automates content processing across seller, buyer, and vendor workflows, accelerating decision-making, enhancing seller experience, detecting fraud, and reducing manual intervention in critical business processes. Key job responsibilities As an Applied Science Manager on the TSI Science team, you will: * Lead development of novel algorithms and modeling techniques advancing the state-of-the-art in multimodal systems * Drive direct customer impact through products and services leveraging vision and language technology * Accelerate team development with multi-modal Large Language Models (LLMs) and GenAI in Computer Vision * Build agentic systems for automation at scale

Basic Qualifications

• - 3+ years of scientists or machine learning engineers management experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Proven experience building machine learning models or developing algorithms for business applications - Proficiency in Java, C++, Python, or related languages - Experience with deep learning libraries (PyTorch, TensorFlow, MxNet) - Research publications in computer vision, deep learning, or machine learning at peer-reviewed venues - PhD, or Master's degree with 5+ years of applied research experience

Preferred Qualifications