Applied Scientist II, Personalization, Grocery P13N
Core
Develop novel machine learning models and features to personalize the grocery shopping journey for hundreds of millions of customers globally using LLM-based techniques and real-time ranking systems.
Role type
Senior Applied Scientist (Personalization)
Builds
LLM-based customer preference models, transformer-based intent prediction models, and large-scale real-time ranking systems for grocery products.
Domain
E-commerce / Grocery / Machine Learning / Large Language Models
Deliverable
production ML models
Required skills
Machine learning model development, Large Language Models (LLMs), Transformer models, Real-time ranking systems, Algorithms and data structures, Numerical optimization, Parallel and distributed computing, High-performance computing, Java, C++, Python
Preferred skills
Unix/Linux, Professional software development
Responsibilities
Innovate new features and models to impact customer experience, Leverage advanced LLM techniques for customer shopping experience at Amazon's scale, Operate on a multidisciplinary team to take ideas from inception to launch, Drive the science roadmap for the team
Seniority
Senior, hands-on IC