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Applied Scientist, AWS NLP

Applied Scientist, AWS NLP

Job ID 
543183
Location 
US-CA-Palo Alto
Posted Date 
7/10/2017

Job Description

Have you ever wanted to work on natural language processing and applied machine learning that will make a lasting impact on society? We are looking for brilliant NLP/ML scientists who have the passion to tackle tough problems by bringing cutting edge machine learning and NLP techniques into a brand new area for Amazon! Together with a highly multi-disciplinary team of scientists, engineers, strategic partners, product managers and subject domain experts you will work on building a product with NLP/ML at its core.

We have positions at different levels of seniority. If you're ready to make a difference, apply today! Or reach out to Ryan Teman at

Basic Qualifications



  • PhD in natural language processing, machine learning or equivalent experience

  • Solid background in statistical learning techniques for NLP (HMMs, CRFs, SVMs, LDA, LSI, MRFs etc)

  • Experience in deep learning

  • Must have ML/NLP algorithm implementation experience as well as the ability to modify standard algorithms (e.g. change objectives, work-out the math and implement)

  • Strong programming skills in at least one object oriented programming language (Java, Scala, C++, Python, etc.)

  • Knowledge of or experience in building production quality and large scale deployment of applications related to natural language processing and machine learning.

  • Fluency with unix

Preferred Qualifications

  • Experience in one or more of the following areas: entity/relation extraction, information extraction, summarisation, semantics, document classification, ontology, question answering, knowledge graph

  • Experience and/or motivation to work on modern deep learning approaches to NLP: word/paragraph embeddings, structured prediction, sentiment analysis, disambiguation

  • Track-record of having developed novel algorithms, e.g. publications in one or more of the following: ACL, NAACL, EMNLP, SIGIR, NIPS, WWW

  • Experience with large scale data analysis tools such as Spark, Hadoop etc