R&D Engineer - ASR

We are looking for a Language Modelling Engineer for our ASR R&D team to work on challenging research problems that have a concrete impact on real-world applications – the work you do will impact real users across the world. Come and join our team of talented engineers and help us to shape the future of AI!

You will perform a role mixing both research and development of cutting-edge technologies by staying current on state-of-the-art algorithms in related fields; evaluating the usage patterns of customers via big data analysis; building models to improve core ASR accuracy of individual products and contributing to the model building codebase.

Principal duties and responsibilities

• Conduct experiments to assess the quality of language models and study the effect of language modelling variants and ancillary natural language processing technology on speech recognition accuracy
• Identify, optimise and cluster training data
• Analyse product usage data to identify areas of possible improvement or enhancement of language modelling processes, methods and NLP techniques.
• Implement improved training recipes and NLP prototypes utilizing primarily Python and/or Perl
• Discuss and present ideas, progress, and results within the research team.
• Improve language modelling performance on Japanese as the focus language

Knowledge, skills and qualifications

Education: Advanced degree (Master’s or PhD) in computer science, computational linguistics, applied mathematics, or a related field

Required skills:

• Background in speech technology, computational linguistics, statistical machine translation and/or natural language processing
• If recently graduated, then relevant experience or internship
• Good software engineering skills, knowledge of scripting languages (e.g. shell scripting, Perl, Python) and experience working under both Linux and Windows
• Solid written and oral communication skills in English
• Native or near-native proficiency in Japanese

Preferred skills:

• Explicit (industry or academic) experience with large vocabulary speech recognition
• Expertise in one or more of the following areas: machine learning, statistical modelling, information retrieval, deep learning, data mining, linguistics.
• Fluent in a third, non-English language