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.

Required Skills & Qualifications
Solid 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.
Solid 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.
Solid 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.

📌 Senior Ai/ml Engineer Hyderabad
🏢 NB Healthcare Technologies
📍 Hyderabad