Applied Scientist II, Amazon Search
Core
Lead science innovation to improve customer search experience by developing high-precision, low-latency search solutions using NLP, ML, and DL.
Role type
Senior IC Applied Scientist (Search & Ranking)
Builds
Scalable search systems, semantic matching models, and ranking architectures for Amazon's global product catalog.
Domain
E-commerce, Search, Natural Language Processing, Machine Learning
Deliverable
production ML models
Required skills
Machine learning model development, semantic matching (bi-encoders, cross-encoders), reinforcement learning, reward modeling, multi-objective ranking, knowledge distillation, quantization, efficient inference strategies, algorithms and data structures, numerical optimization, parallel and distributed computing, high-performance computing
Preferred skills
Unix/Linux usage, professional software development
Technologies
Java, C++, Python, bi-encoders, cross-encoders, foundation models
Responsibilities
Develop and deploy ML models for relevant search results, design and train semantic matching models, develop reinforcement learning and reward-modeling approaches, train multi-objective ranking systems, design scalable model architectures for strict latency constraints, lead end-to-end science projects from formulation to production launch
Seniority
Senior, hands-on IC