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 workplace.
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 (RHEL preferred) on-prem infrastructure
Containerize applications using Docker
Deploy and orchestrate workloads using Kubernetes / OpenShift
Operate within restricted or air-gapped settings
-Understanding of OpenShift AI ecosystem
5. Data & System Integration
Build pipelines integrating structured databases and high-volume logs/streaming data
Support batch and real-time inference architectures
6. Monitoring, Observability & Reliability
Implement end-to-end observability (model + infra)
Use tools like Prometheus, Grafana, ELK stack
Ensure high availability, SLA adherence, and incident response
7. GenAI & Advanced ML Systems
Deploy RAG pipelines and vector databa

📌 Senior Mlops + Devops Engineer Hyderabad
🏢 Accolite Digital India
📍 Hyderabad