MLOps Engineer

Job Description:

We are looking for a hands-on MLOps Engineer to build and operate pipelines that take AI/ML and GenAI models from experimentation to production.

Key Responsibilities:

- Build end-to-end pipelines covering data ingestion, training, evaluation, packaging, versioning, and deployment.

- Develop and maintain Jenkins CI/CD pipelines across Dev, QA, and Production.

- Deploy model-serving APIs on AKS using FastAPI and vLLM.

- Apply ONNX/TensorRT optimization.

- Implement observability using Evidently AI, Prometheus/Grafana, and Azure Monitor.

- Apply DevSecOps practices using Key Vault, Managed Identity, SonarQube, Trivy, and Snyk.

- Develop REST and WebSocket applications using FastAPI.

Tech Stack:

- Languages: Python, Bash, SQL

- CI/CD: Jenkins, Azure DevOps, GitOps, Git

- Cloud/Infra: Azure, AKS, Docker, Helm

- ML/Data: Databricks ML, Delta Lake, MLflow, PySpark, PostgreSQL, Redis, ADLS Gen2

Required Skills:

- 4+ years of ML/AI engineering or DevOps experience.

- Strong production MLOps pipeline experience.

- Strong Jenkins and Azure DevOps experience.

- Knowledge of Azure/AWS/GCP.