Key Responsibilities: • Design cloud-native AI architectures for personalized recommendations, conversational systems, and real-time analytics. • Leverage generative AI technologies like LangChain and RAG to build advanced AI solutions. • Train, fine-tune, and deploy ML models using Microsoft Copilot Studio, Power platform, Azure ML, AWS SageMaker, AWS bedrock • Implement CI/CD pipelines for seamless model updates and scaling. • Build and optimize ETL workflows for large-scale data processing using Azure Data Factory and AWS Glue. • Integrate data pipelines with AI/ML models to enable real-time decision-making. • Deploy robust MLOps practices, including automated monitoring and model retraining. • Enhance AI model security through advanced techniques like LLM Guard and PromptInject. • Collaborate with stakeholders to define AI use cases and ensure alignment with business objectives. • Document AI workflows, data pipelines, and deployment processes for reproducibility.Requirements: • 5+ Years of experience in code development wih Java, Python, Vscode • Proficiency in PyTorch, TensorFlow, and deep learning frameworks. • Experience with Azure Cognitive Services, AWS AI/ML tools, and cloud-native architectures. • Strong understanding of containerization, orchestration, and serverless computing. • Hands-on experience with cloud automation tools like Terraform and Kubernetes. • Proven ability to troubleshoot complex AI/ML workflows and deliver scalable solutions. • Strong leadership and project management skills to handle multi-disciplinary projects. • Solid understanding of NLP, computer vision, reinforcement learning, and time series forecasting.
