Principal Applied Scientist, Alexa AI | Natural UnderstandingJob ID: 2507109 | Amazon.com Services LLC
Are you excited by the idea of joining Alexa AI and playing a leading role in developing cutting-edge NLP technology to empower and delight millions of Alexa users around the world? If so, we'd love to hear from you! The Semantic Parsing team in Alexa AI is seeking a Principal Applied Scientist to advance the state of the art in NLP by solving challenging problems revolving around semantic parsing, the task of parsing natural-language utterances into structured semantic representations. You will collaborate with world-class computer scientists, publish papers, and help to make Alexa smarter and more capable.
A successful candidate will have strong foundations in computer science, mathematics, machine learning, and NLP, with exceptional communication and leadership skills, and a proven track record of technical leadership and delivery under tight deadlines. The candidate must also have hands-on experience with state-of-the-art machine-learning systems, especially in the context of NLP applications.
BASIC QUALIFICATIONSPhD in Computer Science, Electrical Engineering, or MathematicsAt least 6 years of industrial/academic experience in Natural Language Processing and/or Information RetrievalRecent publications (last 4-5 years) in top NLP conferences (ACL, EMNLP, NAACL, EACL, COLING, CoNLL)Extensive experience with Deep Learning frameworks (such as PyTorch or TensorFlow)Excellent written and verbal communication skillsSolid track record of technical leadership and contributions that have advanced the fieldFluency in at least one conventional programming language (Python, C/C++, or Java)PREFERRED QUALIFICATIONSBackground in computational linguistics (including grammar theory, formal semantics, lambda calculus, discourse semantics, etc.)Experience with functional programming languages (ML dialects, Haskell, etc.)Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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