MLOps Engineer

🔧 Key Responsibilities:
• Design & implement end-to-end MLOps pipelines
• Build and manage scalable ML infrastructure on GCP
• Collaborate with Data Science, Data Engineering & DevOps teams
• Ensure seamless deployment, monitoring, and optimization of ML models

✅ Required Skills:
• 5+ years in MLOps / ML Engineering
• Strong Python programming
• Hands-on with GCP services: Vertex AI, GKE, Cloud Run, BigQuery, Cloud Storage, Cloud Composer
• Experience with Docker & Kubernetes
• CI/CD pipelines (GitLab / Bitbucket)
• Terraform (Infrastructure as Code)
• ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Data pipelines & processing (BigQuery, Dataflow, Dataproc, PySpark)

⭐ Nice to Have:
• Vertex AI Pipelines / Kubeflow
• Feature Store experience
• Generative AI & RAG exposure
• Model monitoring & drift detection
• Microservices & API development (Cloud Functions, Cloud Endpoints)
• GCP Certifications