Natural Language Understanding Specialist

2 weeks ago


Johannesburg, Gauteng, South Africa Level-Up Full time

Overview:
You play a key role in training Conversational AI to understand user inputs efficiently. Your responsibilities involve managing training, testing, and optimizing Conversational AI's NLU capabilities, ensuring alignment with conversation design and business logic. We value diverse skills, curiosity, and a thirst for learning, in addition to credentials and work experience, to thrive in this dynamic domain.

Responsibilities:

  • NLU Training, Testing, and Optimization: Oversee the processes of training, testing, and optimizing Conversational AI's NLU capabilities, encompassing creating, curating, and analyzing datasets, and training ML models within the Conversational AI platform.
  • Conversational AI Platform Expertise: Build proficiency in all NLU components of our Conversational AI platform to contribute to R&D initiatives exploring and evaluating NLU features.
  • NLU Architecture: Aid in designing sustainable and scalable NLU solutions within the Conversational AI platform, both templates and custom-built, to ensure precise intent recognition and entity extraction.
  • NLU Strategy: Promote best practices in selecting, designing, and implementing Conversational AI use cases for top-notch language understanding.

Qualifications:

  • Passion for working with language-based data.
  • Proficiency in English.
  • Analytical mindset for organizing and deriving insights from unstructured information and data.
  • Skilled in managing, expanding, and analyzing large language datasets, with an interest in honing expertise in this domain.
  • User-centric problem-solving approach to navigate the ambiguity and noise in open-ended conversations.
  • Keenness to learn and grow on the job, with support from peers, in the rapidly evolving conversational AI sector.

Bonus Qualifications:

  • Experience with conversational AI platforms.
  • Some exposure to software delivery/implementation.
  • Familiarity with fundamental machine learning concepts (classification, clustering, accuracy, precision, recall, overfitting, underfitting).
  • Application of supervised ML techniques to real-world challenges.
  • Sound grasp of user experience design.
  • Familiarity with Regular Expressions (RegEx).
  • Proficiency in baseline statistics and interpreting statistical data.
  • Intermediate or advanced proficiency in other languages, particularly Spanish.


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