Natural Language Understanding (Nlu) Specialist

Overview:   You will play a crucial role in training their Conversational AI to understand user inputs effectively.Your responsibilities will include managing the processes of training, testing, and optimizing our Conversational AI's NLU capabilities, ensuring alignment with conversation design and business logic.We value diversity in skills and encourage curiosity and a passion for learning, alongside credentials and work experience, to excel in this dynamic field.Responsibilities: NLU Training, Testing, and Optimization: Manage the processes of training, testing, and optimizing our Conversational AI's NLU capabilities, including creating, curating, and analyzing datasets and training machine learning models within the Conversational AI platform.Conversational AI Platform Expertise: Develop expertise in all NLU components of our Conversational AI platform to contribute to R&D efforts aimed at exploring and benchmarking NLU features.NLU Architecture: Assist in architecting sustainable and scalable NLU solutions within the Conversational AI platform, both templates and custom-built, to ensure accurate intent recognition and entity extraction.NLU Strategy: Advocate for best practices in selecting, designing, and implementing Conversational AI use cases to achieve high-quality language understanding.Qualifications: Interest in working with language-based data.Advanced knowledge of English.Analytical mindset to organize and make sense of unstructured information and data.Comfortable managing, expanding, and analyzing large language datasets, with an interest in developing expertise in this area.Ability to take a user-centric approach to problem-solving and address the ambiguity and noise inherent in open-ended conversations.Willingness to learn and develop on the job, supported by colleagues, in the rapidly evolving field of conversational AI.Bonus Qualifications: Experience with conversational AI platforms.Some experience in software delivery/implementation.General understanding of machine learning core concepts (classification, clustering, accuracy, precision, recall, overfitting, underfitting).Experience applying supervised machine learning techniques to real-world problems.Decent understanding of user experience design.Exposure to Regular Expressions (RegEx).Comfortable with baseline statistics and interpreting statistical data.Intermediate or advanced knowledge of other languages, especially Spanish.