Key Responsibilities

• Design, build, deploy, and maintain AI/ML applications in production environments
• Develop and fine-tune Large Language Model (LLM) and Generative AI solutions using frameworks like ChatGPT, Llama, and similar
• Implement NLP pipelines for text understanding, classification, summarization, and generation tasks
• Architect and manage end-to-end ML pipelines using MLOps practices and MLflow
• Deploy and monitor ML models on Azure Cloud infrastructure
• Build Retrieval-Augmented Generation (RAG) pipelines using LangChain and vector databases
• Work with vector databases such as Pinecone, FAISS, and ChromaDB for semantic search and embedding management
• Collaborate with data engineers and software teams to integrate AI solutions into production systems
• Leverage Azure Machine Learning and Databricks for scalable model training and experimentation
• Ensure model performance, reliability, and continuous improvement post-deployment

Requirements

• 7 to 15 years of experience in AI/ML engineering
• Strong proficiency in Python for machine learning and AI development
• Hands-on experience with Machine Learning and Deep Learning frameworks
• Expertise in Natural Language Processing (NLP) techniques and pipelines
• Proven experience with Large Language Models (LLMs) and Generative AI — ChatGPT, Llama, or equivalent
• Proficiency in PyTorch or TensorFlow
• Experience deploying ML models to production on Azure Cloud
• Strong knowledge of MLOps practices and MLflow for experiment tracking and model management
• Preferred: Experience with LangChain for LLM orchestration
• Preferred: Hands-on experience with RAG (Retrieval-Augmented Generation) architectures
• Preferred: Familiarity with Azure Machine Learning and Databricks
• Preferred: Experience with vector databases — Pinecone, FAISS, ChromaDB
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related engineering field

Skills Required