The Amazon Search org creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, A9 Product Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day.
Our team's mission is to maximize search quality across all marketplaces in which Amazon operates, by developing required Science and Engineering technologies. We experiment, develop and deploy Classical, Deeplearning and Graph based ML models that leverage multi-modal inputs (Text, Images, etc.) that push the state-of-the-art performance. We innovate to deliver complex models in low latency, low model footprint pipelines.
Our team consists of scientists who have published their work at various Top-Tier external (viz. KDD, WSDM, AAAI, UAI, ECML-PKDD, etc.) and internal conferences.
Key job responsibilities
In this role you will leverage your strong statistical/ML/Deeplearning/NLP background to help build the next generation of our machine learning methods to improve on Search Quality. This role requires a you to be technically pragmatic and ability to deal with complex and abstract problems. The ideal candidate will have experience with machine learning models, graph algorithms, and information retrieval algorithms at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment
· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· Experience programming in Java, C++, Python or related language
· Masters degree in Statistics, Mathematics or related field, or equivalent experience.
· A strong ability in statistical modeling and analysis to provide rigorous solutions that address business needs.
· Excellent data visualization and written communication skills to translate complex models and analysis results into layman terms.
· Hands on development experience in Python, C++, Java, or other OOP language.
· Experience with data visualization technologies, including interactive visualization (i.e. D3js, Bokeh, Matplotlib, FusionCharts, or HighCharts).
· Knowledge of Information Retrieval theory and practice.
· PhD in Computer Science, Statistics, Mathematics or related field, or equivalent professional experience.
· 2+ years of hands-on experience with data analysis for Search, Recommendation, or Advertising space.
· Strong working knowledge of web-scale data processing (e.g., Spark).
· Strong background in machine learning and data mining.
· Experience mentoring/training junior scientists on complex scientific issues.
· Strong verbal and written communications skills; experience presenting complex technical information, succinctly, to technical and business audiences