MLOps Engineer

Key Responsibilities:
Design and implement scalable MLOps pipelines on GCP
Deploy and manage ML models using Vertex AI, GKE, and Cloud Run
Build and manage ETL/ELT pipelines
Work with BigQuery, Dataflow, and Dataproc (PySpark)
Orchestrate workflows using Cloud Composer (Airflow)
Implement CI/CD pipelines and Terraform-based infrastructure
Containerize applications using Docker and Kubernetes
Monitor models for performance, drift, and reliability
Collaborate with Data Science, Data Engineering, and DevOps teams

Mandatory Skills:
Strong GCP experience (Vertex AI, GKE, Cloud Run, BigQuery)
Strong Python programming skills
Hands-on experience with Docker & Kubernetes
Experience with CI/CD pipelines and Terraform (IaC)
Experience with ML frameworks (TensorFlow / PyTorch / Scikit-learn)
Strong knowledge of ETL/ELT pipelines
Experience with Dataflow, Dataproc (PySpark), and BigQuery

Nice to Have:
Experience with Vertex AI Pipelines / Kubeflow
Experience with MLflow and Feature Store
Exposure to Generative AI / RAG / LLM applications
Experience with model monitoring and drift detection
Google Cloud certifications