Applied Scientist II, Amazon Search
Core
Build and ship large-scale relevance and ranking models for natural-language search to interpret complex shopping queries and retrieve relevant products.
Role type
Applied Scientist II (Search Relevance & Ranking)
Builds
Large-scale deep-learning ranking and semantic-matching models for Amazon Search
Domain
E-commerce, Search, Natural Language Processing (NLP)
Deliverable
production ML models
Required skills
Deep learning, Natural Language Processing (NLP), Machine learning, Reinforcement learning, Data mining, Statistics, A/B testing, Large-scale model training, Prototype-to-production deployment
Preferred skills
Information retrieval, Building large-scale ML infrastructure for online recommendation/ads ranking, Publications in ML/IR/NLP venues
Technologies
Java, C++, Python
Responsibilities
Design, train, and ship deep-learning ranking and semantic-matching models; Build training data and evaluation methods (synthetic/historical labels, hard-negative mining); Develop signals matching product attributes to customer queries; Run offline and online A/B experiments; Collaborate with engineers to deploy models at Amazon scale
Seniority
Mid-level IC (PhD or Master's + 2 years experience)
