Senior Applied Scientist, Search Relevance International
Core
Design, develop, and deploy high-performance distributed search systems to maximize search quality and effectiveness for Amazon customers worldwide, specifically focusing on the Relevance India team's expansion efforts.
Role type
Senior Applied Scientist (Search Relevance)
Builds
Production machine-learned ranking models for product search
Domain
E-commerce, Search, Machine Learning
Deliverable
production ML models
Required skills
Machine learning model building, Neural deep learning methods, Java, C++, Python, Hypothesis validation, Low latency model optimization, A/B testing, System design
Preferred skills
R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Large scale distributed systems (Hadoop, Spark)
Responsibilities
Build machine learning models for Product Search; Develop new ranking features and techniques; Propose and validate hypotheses to direct business and product road map; Design, develop, and implement production level code; Collaborate with engineers to solve complex design problems; Mentor team members and set high standards
Seniority
Senior, hands-on IC with mentorship responsibilities