Our mission: To be Earth's most customer-centric company.
Join a mixed science and engineering team reinventing product navigation and discovery on Amazon. As an Applied Scientist II in Personalization, you will lead new initiatives bringing exciting new navigation features to life. This is a greenfield opportunity to join a new thriving team and improve the way millions of customers shop everyday.
You are an Applied Scientist II looking to join a team to develop innovative machine learning, deep learning, natural language processing (NLP), and graph analytics solutions for new category navigation features. You are an experienced applied scientist, have clear communication skills, and get stuff done wickedly fast. You are excited to work on models that will power new navigation features across Amazon. You are an effective teacher and mentor to other scientists. You might desire fully virtual/remote work, or prefer occasional time in the office–both are fine.
About us together:
You will join the new Personalized Shopping Navigation effort to build ML powered personalized navigation features. We will invent scalable new approaches to accurately describe and organize Amazon’s massive breadth of products. We will build new user experiences to make navigating Amazon’s selection more intuitive, seamless and easy. We will build machine learning systems that anticipate what customers are looking for, understanding what they are telling us from their online behavior. We will empower customers to hone in on the exactly what they seek.
You will be working with a group of software and ML engineers on the Shopping Navigator team. The team has Seattle and NY presence with option for full-time virtual work.
Together, we will have massive impact on Amazon customers as well as the company’s bottom line. We are redefining the future of product navigation at the biggest internet retailer on Earth. We hope you’re as excited as we are! Come join us!
Key job responsibilities
- Research and develop novel NLP, machine learning, and graph-based models for information extraction, category identification, category relationships, and customer navigation from the large volumes of Amazon’s product and browse data, search logs, internal/external ontologies and more
- Apply supervised, unsupervised, and reinforcement learning methods to personalize, rank, and optimize category recommendations;
- Establish scalable, efficient, automated processes for Big Data analyses, model development and validation;
- Work closely with software engineers to implement and scale the solutions and to create new navigation experiences for customers;
About the team
We’re a smart, happy, smiley and technically strong bunch. We prioritize having great lives, work life balance, and delivering results. We’re a great team to consider if you’re looking around for ML opportunities with big impact.
- PhD or equivalent Master’s Degree plus 4+ years of experience in CS, CE, ML or related field
- 2+ years of experience of building machine learning models for business application
- Experience programming in Java, C++, Python or related language
• 3+ years of relevant experience in industry and/or academia.
• 3+ years of hands-on experiences in NLP, Recommendation Systems, Information Retrieval/Search, Deep Learning, or a related field
• Strong algorithm development experience and problem solving ability
• Strong written and verbal communication and data storytelling skills
• Experience with distributed machine learning systems
• Ability to take a project from scoping requirements through actual launch of the project
• Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
• A strong sense of curiosity and willingness to learn quickly, building knowledge and skills that this role requires.
. Experience with language transformers, such as BERT, OpenAI GPT
. Experience with distributed ML computing frameworks, such as Spark, MxNet, PyTorch, and/or Tensorflow
• Publications in top venues, such as ACL, ACM, AAAI, KDD, ICML, EMNLP
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.