About the job
The AWS Marketplace team seeks a talented Applied Scientist to lead the development of our next generation of AI-Powered Discovery systems. The ideal candidate excels in translating complex scientific research into practical, high-impact solutions, demonstrating both technical excellence and a deep understanding of customer needs. They should bring proven depth in personalization, search, and recommendations, while remaining committed to mentoring others and fostering a culture of innovation and collaboration. The position offers a unique opportunity to influence how businesses worldwide discover and adopt software solutions.
Responsibilities
Lead the research, design, and development of advanced AI/ML systems for information retrieval and personalized recommendation systems
Identify and evaluate emerging scientific techniques and technologies, translating research into practical, scalable solutions
Drive evaluation and hypothesis testing to continuously improve performance and relevance of search and recommendation systems
Collaborate with cross-functional teams, such as Product and Engineering leaders, to translate scientific innovations into customer value
Mentor Scientists and influence scientific approach across the organization
Qualifications
Minimum
3+ years of building machine learning models or developing algorithms for business application experience
Experience programming in Java, C++, Python or related language
Experience working on recommender systems or personalization within search, e-commerce, shopping, advertising or other related fields
Preferred
PhD in Science, Technology, Engineering, or Mathematics (STEM), or Master's degree and 5+ years of working with or evaluating AI systems experience
Experience conveying complex technical concepts to both technical and business audiences
Experience providing and effectively communicating strategic and tactical recommendations based on data
6+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience