Prometheus, Kafka, Grafana, Docker, Flask, AWS, Jenkins, Gcp, Spark, Python Programming, FastAPI, Rest Apis, Azure, Kubernetes, Airflow, Model monitoring, MLflow, GitHub Actions, Experiment tracking, Vertex AI, Kubeflow, MLOps tools, Data pipelines, RAG pipelines, LLM deployment, LLMOps, real time inference systems, Model versioning, SageMaker, CI CD tools, Feature stores

Devops, REST, MLops, ML pipelines, model deployment, GRPC

Automation Scripting, Databricks, Azure, Kubernetes, Python, LLMOps, MLflow, AKS, Pinecone, vector stores, Chroma, FAISS, RAG pipelines

Yaml, FastAPI, Python, Docker, Ansible, Json, Git, Kafka, MLflow, NVIDIA Triton Inference Server, Airflow, DVC

Jenkins, Docker, Terraform, PowerShell, Azure Databricks, Bash, Kubernetes, Python, Azure DevOps, GitHub Actions, MLflow

Devops, Bash Scripting, MLops, Agile, Software Engineering, deploying AI services securely and efficiently, CI CD workflows, RAG architectures for LLMs, AI integration, DevOps software development principles, Docker containerization, Python REST APIs

Docker, Terraform, Kubernetes, Python, DevOps platform engineering fundamentals, feature stores, Hopsworks, MLflow, Feast, drift detection approaches, ML platforms, SageMaker, automated model training and deployment pipelines, Vertex AI, Kubeflow, Tecton, model monitoring tools

Java, Pyspark, Dynamodb, Kotlin, Tensorflow, Apache Airflow, Git, Pytorch, MLops, Tdd, Python, AWS, scikit-learn, MLflow, Iceberg, SageMaker, Glue, CI CD pipelines, Athena