TL;DR

Applied Scientist (AI): Researching, designing, and developing new AI technologies for personalization with an accent on recommendations, information retrieval, and large language models. Focus on inventing, experimenting with, and launching new features, products, and systems for e-commerce.

Location: Onsite in Tel Aviv, Israel

Company

Amazon's Personalization organization is a high-performing group leveraging machine learning, generative AI, and large-scale data systems to deliver personalized shopping experiences for millions of customers.

What you will do

Research, design, and develop new AI technologies for personalization.
Adopt or invent new machine learning and analytical techniques for recommendations, information retrieval, and large language models.
Collaborate with scientists, engineers, and product partners locally and internationally.
Invent, experiment with, and launch new features, products, and systems that influence the customer shopping journey.

Requirements

PhD in CS/EE or related field, or MSc and 5+ years of applied research experience.
Strong CS foundations, including data structures and algorithms.
Hands-on experience with bringing LLM systems to production.
Excellent coding and design skills, with proficiency in Python.
Several publications at top-tier peer-reviewed research conferences or journals.
Strong communication and collaboration skills.

Nice to have

Experience in building and launching deep learning and machine learning models for business applications.
Solid knowledge of big data and cloud technologies (e.g., Spark, AWS).
Experience with information retrieval, recommender systems, natural language processing, and/or personalization algorithms.
Publications at top Web, Machine Learning, or Natural Language Processing conferences such as KDD, ICML, NeurIPS, ACL, EMNLP.

Culture & Benefits

Inclusive culture that empowers Amazonians to deliver results for customers.
Opportunity to innovate on behalf of millions of customers and influence the future of e-commerce.
Access to large datasets and tremendous computational resources.
Support for workplace accommodation or adjustment during the application and hiring process, including for disabilities.