Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Large Language Models
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready application pipelines, ensuring high-quality outputs. You will also explore the integration of generative AI models into solutions, which may encompass various advanced technologies such as deep learning, neural networks, chatbots, and image processing. Collaboration with cross-functional teams will be essential to ensure the successful deployment of these innovative solutions. Roles & Responsibilities: - Expected to be an SME. - Collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Mentor junior team members to enhance their skills and knowledge. - Continuously evaluate and improve existing processes and workflows. Professional & Technical Skills: -Experience in Java and Python -Experience in AI application development, focusing on cloud-based AI model integration, deployment, and optimization. -Proficiency in programming languages such as Python, Java, and experience with AI/ML frameworks like Spring AI, LangChain, LangGraph, LlamaIndex, Agno, Pydantic, TensorFlow etc. -Hands-on experience with Azure Cloud Services for AI, including Azure OpenAI and Azure AI Search for developing and deploying AI applications at scale. -Proficiency in advanced AI architecture patterns, including Retrieval-Augmented Generation (RAG), Agentic RAG, MCP, Functional Calling, A2A especially in an Azure environment. -Experience in prompt engineering, context engineering, vector databases, embedding/chunking strategies, and real-time data integration. -Experience in evaluating model output and optimization" Additional Information: - The candidate should have minimum 5 years of experience in Large Language Models. - A 15 years full time education is required.

15 years full time education

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