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Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we use machine learning and cluster-computing technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing .You will encounter many challenges, including:
- Scale (build models to handle billions of pages), - Accuracy (extreme requirements for precision and recall)You will help us to
- Build a scalable system which can algorithmically extract information information from world wide web
- Intelligently cluster web pages, segment and classify regions , extract relevant information and structure the data available on semi-structured web pages
- Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents.Key job responsibilities- Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes
- Design, develop, evaluate and deploy, innovative and highly scalable ML models- Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance
- Leading projects and mentoring other scientists, engineers in the use of ML techniques
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
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