Job Responsibilities:

• Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems.
• Use & build vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.
• Fine-tuned and optimized use of large language models.
• Implement and experiment with powerful NLP, NLU, and NLG techniques to enhance the capabilities and performance of our conversational AI products.
• Conduct research and stay abreast of the latest advancements in machine learning, NLP, and conversational AI to drive innovation and maintain competitive advantage.

Job Requirements

• Bachelor’s degree in computer science, Artificial Intelligence, Machine Learning, or a related field.
• 3+ years of experience in machine learning engineering, with a focus on building and deploying conversational AI solutions.
• Confirmed expertise in developing RAG models, working with vector databases, and fine-tuning large language models.
• Strong programming skills in Python and proficiency with machine learning libraries such as TensorFlow, PyTorch, or JAX.
• Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation.
• Strong problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems.
• Strong communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders