Applied Science Manager, Personalization

Description

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon.

Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at Amazon scale and latency requirements. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future.

As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership.

Please visit https://www.amazon.science for more information.

Basic Qualifications

• PhD or equivalent research experience, or Master's degree
• 3+ years of scientists or machine learning engineers management experience
• 3+ years of building machine learning models for business application experience
• Experience leading applied research in one or more of: Recommendation Systems, Information Retrieval, NLP, or Large Language Models
• Demonstrated ability to think strategically, communicate effectively (written and verbal) with senior leadership, and drive cross-team collaboration
  
  

• Experience working on recommender systems or personalization within search, e-commerce, shopping, advertising or other related fields
• Experience with LLM training, fine-tuning, or adaptation (e.g., tokenizer modification, domain adaptation)