Senior AI / ML Engineer

AI/ML Architecture Development Implement and deploy machine learning models in production environments Work with generative AI models and NLP techniques (e.g., OpenAI, Claude APIs) Apply prompt engineering and retrieval-augmented generation (RAG) techniques Build end-to-end ML workflows from data preprocessing to model evaluation Contribute to the development of conversational AI solutions Software Engineering Data Pipeline Development Design, build, and maintain data pipelines and end-to-end ML workflows. Build and deploy web services that integrate ML models Implement APIs using frameworks like FastAPI or Flask Work with databases (preferably MySql) and data processing tools Ensure code quality, performance, and security in all implementations Deployment Integration Build production-grade ML models and APIs and deploy them on cloud platforms with the help of the DevOps team. Ability to Monitor, analyze, and optimize the performance of deployed models and data workflows with the help of Devops team Collaboration Work closely with cross-functional teams including data scientists and software engineers Contribute to a culture of learning and innovation Adapt to challenges even when requirements are ambiguous Technical Requirements: Programming Frameworks: Strong proficiency in Python with hands-on experience in TensorFlow, PyTorch, Keras, and related ML libraries/Ecosystem. Experience with data science tools (pandas, NumPymatplotlib, scikit-learn) Generative AI Expertise: Knowledge of generative AI models and frameworks, including OpenAI APIs, LangChain, LangGraph, Hugging Face Transformers, and related technologies. Experience in fine-tuning large language models (LLMs) and implementing RAG systems leveraging vector databases like Pinecone or similar. Experience in developing multi-agent Retrieval-Augmented Generation (RAG) applications, integrating automated workflows to streamline data retrieval,processing, and response generation. API Development: Experience in developing and deploying APIs using frameworks like FastAPI or Flask. Qualifications: Bachelor s degree in Computer Science, Engineering or related field. 5+ years of hands-on experience in AI/ML engineering, with expertise in generative AI and data engineering. Excellent problem-solving, analytical, and communication skills. Ability to work independently in a fast-paced, dynamic environment while effectively collaborating with cross-functional teams.