Technical Consultant
6 days ago
Responsibilities Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation in conversational AI systems. Build and deploy intelligent AI agents capable of handling multi-turn conversations, executing autonomous tasks, integrating external APIs, and managing tool invocation based on user intent and context. Design and deploy a Model Context Protocol that facilitates seamless, standardized connectivity and data sharing between AI systems and external platforms, APIs, and databases. Use and 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. #J-18808-Ljbffr
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