Language Engineer (French) - Amazon Alexa (m/f) - Amazon - Berlin - Wizbii

Language Engineer (French) - Amazon Alexa (m/f)

  • Durch Amazon
  • Berlin (Deutschland)
  • Ingenieurwesen / Produktionsmanagement
2018-09-05T00:43:25+0000

Job description

DESCRIPTION

Interested in Amazon Echo? Come work on it. We’re building the speech and language solutions behind Amazon Alexa and other Amazon products and services. Come join us!

As a Language Engineer (French) in our Applied Modeling team, you will be responsible for data-driven improvements to our spoken language understanding models. Your work will directly impact our customers in the form of products and services that make use of speech and language technology.

You will:
· Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.
· Clean, analyze and select data to achieve goals
· Build and release models that elevate the customer experience and track impact over time
· Collaborate with colleagues from science, engineering and business backgrounds
· Present proposals and results in a clear manner backed by data and coupled with actionable conclusions
· Work with engineers to develop efficient data querying infrastructure for both offline and online use cases

Seeked profile

BASIC QUALIFICATIONS

· Bachelor’s or Master’s degree in a relevant field
· Fluency in French language, both oral and written
· 2+ years’ experience with various data analysis and visualization tools
· Experience using Python, Perl, or another scripting language; command line usage
· Experience diving into data to discover hidden patterns and conducting error analysis
· Experience applying various machine learning techniques and understanding the key parameters that affect their performance
· Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, and the ability to accurately determine cause and effect relationships
· Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.

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