Senior Lead AI/ML Engineer - R01573662

• Dialogue Design, Syntax and semantic analysis, Reinforcement learning, Text Classification, Governance for Conversational AI, RASA, Natural Language Understanding (NLU), Kore.ai, GDF (Google Dialog Flow), IBM Watson, Automatic Speech Recognition (ASR), Dialogue Management (NLG), Spark NLP, Recurrent Neural Networks, Conv AI Testing

Job requirements

• Experience Range: With at least 5-8 years of experience in data science, including 2 years specifically in conversational AI technologies and agentic AI development Key Responsibilities: 1. Evaluate agent output results and EVal tests to ensure accuracy and relevance in conversational AI applications 2. Design and execute functional and AI quality testing, including grounding, unsupported-response, contradiction, and scenario validation 3. Develop and optimize AI models for dialogue management, syntax and semantic analysis, and reinforcement learning 4. Collaborate with engineering and product teams to define AI deployment paths and integrate agentic AI solutions into production environments 5. Implement governance frameworks for conversational AI to maintain compliance and quality standards 6. Utilize platforms such as RASA, Kore.ai, Google Dialog Flow, and IBM Watson to build and refine conversational agents 7. Apply advanced text classification and natural language understanding techniques to enhance AI translation and conversation capabilities 8. Conduct scenario-based validation and troubleshooting to continuously improve conversational AI performance Required Skills: 1. Hands-on experience with RASA 2. Proficiency with Natural Language Understanding (NLU) 3. Experience with Google Dialog Flow 4. Working knowledge of Kore.ai 5. Familiarity with IBM Watson for conversational AI 6. Strong proficiency in syntax and semantic analysis using Python or relevant libraries 7. Experience with reinforcement learning algorithms (e.g., Q-learning, policy gradients) 8. Advanced text classification techniques (e.g., transformers, BERT, LSTM) 9. Experience in dialogue design for conversational AI platforms Preferred Skills: 1. Experience with Automatic Speech Recognition (ASR) integration 2. Advanced skills in Natural Language Generation (NLG) 3. Proficiency in Spark NLP for text processing 4. Hands-on experience with Recurrent Neural Networks (RNNs) 5. Background in conversational AI testing methodologies and scenario validation Desired Qualifications: 1. Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a closely related discipline 2. Certification in Machine Learning, Natural Language Processing, or Conversational AI from recognized institutions 3. Relevant certification in conversational AI platforms such as RASA or Google Dialog Flow

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