About This Role 5 to 9 years of experience Skills: MLOps + DevOps, AI/ML platforms, Linux, Docker, Kubernetes Role Overview: We are looking for a Senior MLOps + DevOps Engineer (6+ years) to architect, build, and scale AI/ML platforms in an on-prem enterprise environment. This role requires end-to-end ownership of ML systems, infrastructure, CI/CD, and production reliability, enabling scalable deployment of machine learning and GenAI solutions. Key Responsibilities: 1. Platform Architecture & Ownership - Design and own end-to-end ML platform architecture (data training deployment monitoring) - Define and enforce best practices for scalable and secure ML systems - Standardize MLOps + DevOps frameworks and processes -AI/ML Platform Architecture deployed and should be able to explain it clearly. -Ability to design scalable ML/data platforms end-to-end -Explain real-world integration patterns using Kafka, especially on-premise setups. 2. Model Deployment & Serving - Deploy and manage ML/LLM models on GPU-based on-prem infrastructure - Optimize inference performance (latency, throughput, batching) - Implement model versioning, A/B testing, and rollback strategies 3. CI/CD & Automation - Design and implement CI/CD pipelines for ML models, APIs, and data workflows - Enable automated testing, deployment, and release management 4. Infrastructure & Containerization - Manage Linux-based (…