Description

 Key Responsibilities

Design, develop and deploy AI/ML models to solve complex business problems using structured and unstructured data.Build predictive models using machine learning, statistical modeling, feature engineering and advanced analytics techniques.Develop Generative AI and LLM-based solutions, including RAG, prompt engineering, embeddings and vector-search-based applications.Perform data exploration, cleansing, preprocessing, feature selection and model evaluation using Python, Pandas, NumPy and Scikit-learn.Develop deep learning solutions using frameworks such as PyTorch or TensorFlow where required.Work with LLMs and AI platforms such as Azure OpenAI, along with frameworks such as LangChain/LlamaIndex when appropriate.Design and evaluate RAG pipelines, including document processing, chunking, embeddings, retrieval and response-quality evaluation.Develop and integrate AI services using REST APIs and collaborate with engineering teams to productionize models.Implement MLOps practices covering model versioning, deployment, monitoring and continuous improvement.Collaborate with business stakeholders, data engineers, architects and application teams to translate business requirements into scalable AI solutions.Required SkillsStrong programming experience in Python and SQL.Strong knowledge of Machine Learning, NLP, statistical modeling and predictive analytics.Hands-on experience with Generative AI, LLMs, RAG, prompt engineering and embeddings.Experience with Scikit-learn, PyTorch and/or TensorFlow.Good understanding of vector databases/search technologies and semantic search.Experience with Azure AI/Azure OpenAI or equivalent cloud AI platforms.Knowledge of MLOps, model deployment, APIs and production AI architectures.Strong analytical, problem-solving and stakeholder communication skills

Key Skills

Education

Bachelor's degree