**Introduction** In this role, you’ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology. **Your role and responsibilities** − Design and implement data pipelines for collecting, processing, and transforming data relevant for RAG and model evaluation. − Develop and manage data indexing and search systems (e.g., Vector Databases, Elasticsearch, Pinecone) for efficient Retrieval in RAG. − Select, train, and optimize ML models to enhance chatbot functionality (e.g., for intent understanding, entity extraction, sentiment analysis, if relevant). − Design and implement methodologies for evaluating the performance of RAG models, conversational flows, and the overall chatbot user experience. − Monitor model performance in production and implement strategies for retraining and improvement. − Collaborate with Business/Technical Analysts to understand business metrics and translate them into technical metrics. − Ensure data quality and integrity. **Required technical and professional expertise** − Minimum of 4 years of experience in Machine Learning Engineering or Data Science with an emphasis on NLP. − Expert knowledge of Python and relevant ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). − In-depth knowledge of NLP and RAG (Retrieval Augmented Generation) concepts. − Experience with vector databases and search engines (e.g., Milvus, Pinecone, Elasticsearch). − Practical experience with GCP AI/ML services (Vertex AI, BigQuery ML, Cloud Natural Language API, Cloud AI Platform). − Google certification "Generative AI Leader", " Data Practitioner" , "Machine Learning Engineer", "Cloud Database Engineer", "Data Engineer", "Cloud Security Engineer" − Experience with data pipelines and ETL processes. − Strong analytical skills and the ability to interpret complex datasets. − Experience with A/B testing and experimental design for ML models. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.