MLops, Gcp, Autoscaling, Containers, Azure, Kubernetes, Python, AWS, ML infrastructure, distributed training, inference optimization, quantization

DataFlow, Sql, Python, Cloud Run, Workflow Composer, Cloud SQL, Log explorer, GCP services, Pub Sub, Error reporting, Big Query

PostgreSQL, Containers, Kafka, Neo4j, MongoDB, FastAPI, Cosmos DB, Azure, API-based model integration, K8S, secure deployment practices, observability needs, DevOps tooling, RAG agentic workflows, environment management, CI CD pipelines, AI solutions