Source description
About the role
Responsibilities
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Responsible for building and maintaining machine learning models to identify end user intent for a multi-channel Virtual Assistant
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Understand the intent portfolio for NLU across domains (e.g., technology, human resources) and how it maps to conversation design for web, mobile, and voice channels
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Identify and build appropriate datasets to train and test machine learning models for intent classification and speech recognition
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Develop tools and telemetry that can measure/monitor accuracy and performance and update the models accordingly throughout development lifecycle
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Develop disambiguating and error handling strategies as the virtual assistant scales
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Monitor conversations in the application to identify underperforming content and develop solutions to improve the performance
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Collaborate with data scientists, product owners, UX researchers, and engineers to build out the "brain" of the virtual assistant
Requirements
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Experience with conversational interfaces and natural language processing
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Experience training machine learning algorithms for data classification and/or speech recognition
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Experience improving intent recognition of a data classification model
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Experience with Python
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Unique skillset in computational linguistics and technical experience
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Familiarity with LLMs
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Familiarity with using version control technologies such as Git, SVN, or JIRA
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Experience in DevOps and Agile methodology
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Strong analytical and troubleshooting skills
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Desired skills:
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Experience with Generative AI
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