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Principal Machine Learning Scientist - Machine Translation

Company name, Inc.

Pittsburgh, PA

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Job DescriptionPrincipal Machine Learning Scientist for Machine TranslationAmazon is looking for a passionate, talented, and inventive senior scientist with a strong background in applying machine learning and data-driven methods to Machine Translation (MT) and Natural Language Processing (NLP), to help build our industry-leading MT and NLP technology.Our mission is to enable superior experience for all of Amazon\u2019s customers in their native languages by developing state-of-the art technology and applications in Machine Translation (MT), Natural Language Processing (NLP) and Machine Learning (ML).As part of our MT R&D team, you will take on a leading role in driving our MT R&D strategy in the area of Neural Machine Translation in 2018 and beyond. You will work alongside our other internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in Neural MT. Your work will directly impact millions of our customers in the form of products and services that make use of our MT and NLP technologies. You will gain hands on experience with Amazon\u2019s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in MT and NLP.Major responsibilities:

In close collaboration with management, lead the development of a strategic R&D roadmap in the area of Neural Machine Translation by identifying and prioritizing high-value R&D projects that lead to major breakthroughs in the capabilities of state-of-the art Neural MT systems.
Apply advanced machine learning methods to design and implement scalable MT and text understanding systems that significantly advance the state-of-the-art.
Design, development and evaluation of highly accurate and innovative models for translation and for language analysis and generation.
Work closely with software engineering teams to drive large-scale and real-time model implementations and new feature capabilities.
Establish scalable, efficient, automated processes for large-scale data analysis, model development, model validation and model implementation
Research and implement novel scalable machine learning approaches.
Present R&D plans and outcomes internally to senior management and to peer teams within Amazon and externally at top academic and industry comferences and meetings.

Basic Qualifications

PhD in Computer Science, Computational Linguistics, Machine Learning, Statistics or in another highly quantitative field
Demonstrated independent scientific thinking and/or a track record of thought leadership and contributions that have advanced the field
Established publication record in MT, NLP and/or related fields.
3 years of post-graduate experience in leading major R&D projects in the area of MT and/or NLP in an academic or industrial lab setting.
5 years of experience in developing data-driven predictive modeling and analysis in MT, NLP or other related language technology areas.
Excellent implementation skills in Java, C (or other high-level programming language) as well as Python or similar scripting languages.

Preferred Qualifications

5 years of experience in R&D in large-scale NLP systems in a large industrial or government environment
Solid software development experience
Excellent written and spoken communication skills.
A curiosity about problems that seem impossible to solve and a drive to think outside of the box to invent what hasn't been invented yet.

Company info, Inc.
Website :

Company Profile
Amazon, a Fortune 500 company based in Seattle, Washington, is the global leader in e-commerce. Since Jeff Bezos started Amazon in 1995, we have significantly expanded our product offerings, international sites, and worldwide network of fulfillment and customer service centers. Today, Amazon offers everything from books and electronics to tennis rackets and diamond jewelry. We operate sites in Canada, China, France, Germany, Italy, Japan, Spain and United Kingdom and maintain dozens of fulfillment centers around the world which encompass more than 26 million square feet.

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