ROLES AND RESPONSIBILITY Design train and deploy AI ML models including offline deployment for enterprise use cases Integrate AI models into enterprise applications using cloud-native architectures Implement data pipelines feature engineering and model evaluation frameworks Optimize models for performance scalability and cost-efficiency Ensure security compliance and governance in AI solutions Train and mentor team members on AI ML concepts tools and best practices Collaborate with product and engineering teams to deliver AI-driven features DESIRED SKILLS 5 years in enterprise software development with solid coding skills e g Python NET or Java 2 years in ML AI model training evaluation and deployment Hands-on experience with enterprise cloud platforms Azure AWS or GCP and relevant AI services Proven experience in at least one end-to-end AI project involving offline model deployment Strong understanding of data preprocessing feature engineering and model optimization Familiarity with MLOps practices CI CD for ML model versioning monitoring GOOD TO HAVE Experience with Azure AI Services Azure ML or equivalent cloud AI platforms Knowledge of vector databases RAG architectures and LLM integration Familiarity with containerization Docker Kubernetes and IaC Terraform Bicep Exposure to Responsible AI principles and compliance frameworks TOOLS TECHNOLOGIES ML AI TensorFlow PyTorch Scikit-learn ONNX Cloud Azure ML AWS SageMaker GCP Vertex AI DevOps MLOps GitHub Actions Azure DevOps MLflow Kubeflow Data SQL NoSQL databases Data Lakes Feature Stores EDUCATION BE BTech MCA or equivalent in Computer Science or related field WORK LOCATION Full-time position based in Raipur Pune