MLOps Engineer

We are looking for a hands-on MLOps Engineer who will work closely with Data Scientists and ML Engineers to build, deploy, monitor, and optimize machine learning models in production.
This role is NOT focused on platform engineering or infrastructure-only work—instead, it emphasizes end-to-end ML lifecycle management, model deployment, and operationalization of ML systems.

Technical Requirements: Exposure to cloud platforms (AWS / Azure / GCP) for ML deployment
Knowledge of LLMOps / GenAI deployment pipelines
Familiarity with:

Feature stores
Data pipelines (Spark, Kafka)
Experience with Kubernetes (basic deployment level)

Additional Responsibilities: Experience with real-time inference systems
Exposure to monitoring tools (Prometheus, Grafana)
Knowledge of LLM deployment / RAG pipelines