Summary: 

Evaluate the usage patterns of customers via big data analysis; build models to improve core ASR accuracy of individual products; contribute to the model building codebase, including our deep learning toolkit; and stay current on state-of-the-art algorithms in related fields. Work on challenging research problems that have a concrete impact on real-world applications, such as in-car assistants and home entertainment systems.     Responsibilities: - Conducting experiments to assess the quality of language models and study the effect of language modeling variants and ancillary natural language processing technology (such as auto-punctuation) on speech recognition accuracy. - Identifying, optimizing, and clustering training data. - Analyzing product usage data to identify areas of possible improvement or enhancement of language modeling process, method, and NLP techniques. - Implementation of improved training recipes and NLP prototypes utilizing C/C++, Perl, and Python. - Discussing and presenting ideas, progress, and results within the research team - Improving language modeling performance in multiple languages, especially Chinese  Required Skills: - Background in speech technology, statistical machine translation, or natural language processing - Excellent programming skills (C/C++, Python) with knowledge of standard data structures and algorithms - Experience using Unix/Linux and shell scripting - Solid written and oral communication skills (English) - Native Chinese fluency is a must 

Preferred Skills: - Explicit (industry or academic) experience with large vocabulary speech recognition - Expertise in one or more of the following areas: machine learning, statistical modeling, deep learning, numerical optimization, data mining, algorithm design, software engineering, computational linguistics 

Education:

PhD or MS , major in computer science, computational linguistics, applied mathematics, or a related field  .