Senior Applied Scientist, Amazon Core Search
Core
Lead science innovation to improve customer search experience through high-quality autocomplete search suggestions and results.
Role type
Senior Applied Scientist (Search & NLP)
Builds
Scalable search autocomplete systems, semantic matching models, and ranking/scoring systems for Amazon's global product catalog.
Domain
E-commerce, Search, Natural Language Processing, Machine Learning
Deliverable
production ML models
Required skills
Neural deep learning, machine learning, semantic matching, reinforcement learning, reward modeling, multi-objective ranking, knowledge distillation, model quantization, efficient inference, Java, C++, Python
Preferred skills
Large scale distributed systems, modeling tools (R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy)
Responsibilities
Develop and deploy ML models for diverse search autocomplete suggestions; Design and train semantic matching models (bi-encoders, cross-encoders); Develop reinforcement learning and reward-modeling approaches; Train multi-objective ranking and scoring systems; Design and implement scalable model architectures optimized for strict latency constraints; Lead end-to-end science projects from problem formulation through production launch.
Seniority
Senior, hands-on IC with strategic vision