What you ll be doing: Design, train, and optimize AI models specifically for real-time content summarization and recommendation. Implement advanced Natural Language Processing (NLP) techniques to enhance conversational UI and predictive interactions. Apply Retrieval-Augmented Generation (RAG) for intelligent response generation from dynamic content sources. Fine-tune transformer-based models (e.g., BERT, T5) using domain-specific datasets to achieve optimal performance. Collaborate closely with backend and data engineering teams to streamline model deployment within a production-grade environment. Ensure that brand tone and content accuracy are meticulously maintained throughout all AI-generated outputs.

Preferred Qualifications: Understanding of branding, tone, and the user experience (UX) implications in AI-generated content. Experience working with headless CMS (Content Management Systems) and structured content datasets. Knowledge of ethical AI principles and prompt engineering best practices.

Desired Candidate Profile

Who we re looking for: We are seeking an experienced AI/ML Engineer with a minimum of 5 years of expertise to join our innovative technology team. In this pivotal role, you will be responsible for designing, training, and optimizing AI models, with a strong focus on Natural Language Processing (NLP) for real-time content summarization, recommendation, and conversational UIs. You will implement cutting-edge techniques like Retrieval-Augmented Generation (RAG) and fine-tune transformer-based models, collaborating closely with backend and data engineering teams to ensure seamless deployment and maintenance of brand tone and content accuracy in all AI outputs.

What you ll need: Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field. 5 7 years of progressive experience in AI/ML engineering, with a strong and proven focus on Natural Language Processing (NLP). Strong practical experience with leading Machine Learning frameworks such as TensorFlow, PyTorch, and Hugging Face. Experience with LangChain and LangGraph. Experience with MLOps pipelines and platforms like AWS SageMaker, Azure AI Search, or similar. Solid understanding of Large Language Models (LLMs), embeddings, and semantic search technologies. Expert proficiency in Python and robust data handling libraries such as Pandas and NumPy. Familiarity with deploying AI models via microservices or APIs.