🎯 Position Objective
Ensure the industrialization, automation, and reliability of data science pipelines in a hybrid AWS/GCP cloud environment.
🛠️ Main Responsibilities
🔹 DevOps
Design and maintain CI/CD pipelines (GitLab CI, GitHub Actions, Jenkins).
Manage infrastructure using Terraform.
Deploy and monitor containerized applications (Docker, Kubernetes, Helm).
Implement monitoring solutions (Prometheus, Grafana, CloudWatch, Stackdriver).
Secure cloud environments (IAM, KMS, secret management).
🔹 MLOps
Develop and orchestrate ML & AI pipelines (Airflow, Vertex AI Pipelines, etc.).
Deploy models to production (Vertex AI Endpoints).
Collaborate with data scientists to automate the model lifecycle.
🧰 Technical Environment
Cloud: AWS (S3, SageMaker, EKS), GCP (BigQuery, Vertex AI, GKE)
IaC: Terraform
SaaS: Snowflake
PaaS: Dataiku
CI/CD: GitLab CI, GitHub Actions
Containers: Docker, Kubernetes
Languages: Python, Bash, YAML
Monitoring: Prometheus, Grafana, CloudWatch, Stackdriver
ML Tools: Airflow, Kubeflow, Vertex AI, SageMaker