In the Amazon Product Knowledge Team, we are building comprehensive schematic and semantic constructs to understand customer intent, in order to provide a delightful experience that feels targeted to their shopping mission. It expands beyond factual product characteristics (e.g. resolution of a TV) to additional dimensions used in customer shopping missions: what the product is used for (e.g. baby-proofing), where the product is used (e.g. kitchen), who uses the product (e.g. teenager), when the product is used (e.g. thanksgiving), and opinions about the product (e.g. cute t-shirt). We build scalable solutions that are partially or entirely powered by AI and ML to discover Product Knowledge by mining customer engagements (e.g. search queries, customer reviews, web pages … etc.).
We have multiple positions for applied scientists who are excited to work on big data challenges including; web scale data integration, natural language processing, discovery of new relationships along with their semantics, knowledge inferencing and enhancement, knowledge embedding, entity recognition, and improving data quality to support strategic and tactical decision-making in building Product Knowledge.
We are looking for applied scientists with experience in building practical solutions who can work closely with software engineers to ship and automate solutions in production. Our applied scientists also collaborate and partner with teams across Amazon to understand and reflect on how to create benefit for every customer.
· PhD degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
· 3+ years of experience in building machine learning models for business application
· Experience programming in Java, C++, Python or related language
- 5+ years of hands-on experience in knowledge creation, inferencing, embedding, processing; NLP, web scale data integration, and/or data quality.
- Masters in Computer Science, Machine Learning, Data Quality, Statistics or a related field
- A strong interest and passion about data (the solutions and ideas are just means to get and produce good-useful data and knowledge)
- Algorithm development experience
- Experience mentoring and training others on complex technical issues
- Experience with transfer learning, deep learning and/or reinforcement learning
- PhD in Computer Science, Machine Learning, Data Quality, Statistics or a related field.
- Experience building systems and tools that perform large scale data analysis.
- Excellent communication and presentation skills.
- Experience with Java, Scala, Python.
- Experience with distributed data processing platforms such as Spark, MapReduce, and high-level query languages such as SQL, Hive, or Pig.
- Experience with ML packages and systems, deep learning, Tensor-Flow, SciKit, XGBoost ... etc.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation