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Job Title: Senior AI/ML Engineer Experience: 10+ Years Location: Hyderabad, India Employment Type: Full-time Role Summary: We are looking for a highly experienced Senior AI/ML Engineer with strong hands-on expertise in designing, developing, deploying, and monitoring enterprise-scale AI/ML systems. The candidate must possess end-to-end experience across the complete AI/ML lifecycle, including model development, deployment, observability, governance, optimization, and production support. Key Responsibilities: • Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions. • Build and optimize end-to-end ML pipelines including experimentation, deployment, monitoring, and retraining. • Develop scalable inference architectures, vector search systems, and RAG-based applications. • Implement observability, monitoring, governance, and production support mechanisms for AI systems. • Drive model lifecycle management including versioning, experimentation tracking, and CI/CD automation. • Mentor engineering teams and establish AI/ML engineering best practices. • Collaborate with business stakeholders to identify and implement AI-driven solutions. • Optimize AI systems for scalability, latency, reliability, and cost efficiency. • Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions. • Build and optimize end-to-end ML pipelines including experimentation, deployment, monitoring, and retraining. • Develop scalable inference architectures, vector search systems, and RAG-based applications. • Implement observability, monitoring, governance, and production support mechanisms for AI systems. • Drive model lifecycle management including versioning, experimentation tracking, and CI/CD automation. • Mentor engineering teams and establish AI/ML engineering best practices. • Collaborate with business stakeholders to identify and implement AI-driven solutions. • Optimize AI systems for scalability, latency, reliability, and cost efficiency. Required Skills & Qualifications: • Strong hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI systems. • Extensive experience in end-to-end ML lifecycle including data ingestion, feature engineering, model development, validation, deployment, monitoring, and retraining. • Hands-on expertise with Python, SQL, APIs, and ML frameworks such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain. • Experience with Vector Databases, RAG pipelines, semantic search, embeddings, and LLM orchestration. • Strong expertise in MLOps tools including MLflow, DVC, Docker, Kubernetes, CI/CD pipelines, and model versioning. • Hands-on experience with observability, logging, tracing, monitoring, drift detection, and model performance tracking. • Experience building scalable cloud-native inference and AI deployment pipelines. • Strong understanding of distributed systems, data engineering, and scalable AI infrastructure. • Excellent stakeholder management and cross-functional collaboration skills. • Experience with Azure Cloud Stack is a plus