Senior MLOps Engineer - Azure Cloud Infrastructure

Description :

Key Skills : Kubernetes, vLLM, ML Model deployment, CI/CD pipeline for Model tuning,

Model lifecycle management in Azure

About the Role :

We are looking for a hands-on MLOps Engineer who can take ML models from notebook chaos to production reality.

Youll own the end-to-end ML deployment pipeline from training orchestration to scalable inference using Kubernetes, vLLM, CI/CD automation, and Azure ML services.

If you love automating everything, optimising inference performance, and building rock-solid ML infrastructure, then this role is for you.

Key Responsibilities :

Model Deployment & Serving :

- Deploy and manage ML/LLM models in production using Kubernetes

- Implement high-performance inference pipelines using vLLM / Triton / REST & gRPC APIs

- Optimize model latency, throughput, GPU utilization and autoscaling

CI/CD for ML Pipelines :

- Build automated CI/CD pipelines for model training, tuning, validation and deployment

- Integrate GitHub Actions / Azure DevOps / Jenkins for continuous integration

- Enable automated rollback and versioning of ML models

Model Lifecycle Management :

- Manage full ML lifecycle including training, experiment tracking, model registry, deployment, monitoring and retraining

- Implement model version control, data drift detection and performance monitoring

- Automate scheduled retraining workflows

Azure Cloud & Infrastructure :

- Design and maintain ML infrastructure on Microsoft Azure (Azure ML, AKS, Blob Storage, ACR, Key Vault)

- Manage GPU clusters, networking, secrets and resource optimization

- Implement secure production-grade architecture

Monitoring & Reliability :

- Implement monitoring using Prometheus, Grafana, Azure Monitor

- Track inference metrics, system health and model performance

- Ensure high availability and fault tolerance

Required Skills :

Core MLOps Skills :

- Strong experience with Kubernetes (AKS preferred)

- Experience deploying ML/LLM models using vLLM / FastAPI / TorchServe / Triton

- Hands-on experience with CI/CD pipelines for ML workflows

- Experience with model versioning and lifecycle management tools

Cloud & DevOps :

- Strong hands-on with Azure Cloud services

- Experience with Docker, Helm, Terraform (good to have)

- Knowledge of infrastructure automation and scaling

Programming & Frameworks :

- Strong Python skills

- Experience with PyTorch / TensorFlow / HuggingFace

- REST API development for model serving