About The Role You will join a team responsible for building and scaling the ML platform used by 300+ data scientists and ML engineers across 60+ teams. Your work will directly impact how machine learning models are deployed to production — reliably, securely, and at scale.
You’ll spend most of your time implementing and standardising Databricks MLOps (environments, CI/CD pipelines, model monitoring) while also contributing to the evolution of a battle‑tested AWS Sage Maker platform. You Day-to-day Design, build, and scale a production-grade ML / MLOps platform
Implement Databricks MLOps (environments, CI/CD pipelines, monitoring)
Maintain and improve the AWS Sage Maker ML platform
Automate infrastructure and workflows using Python and Infrastructure‑as‑Code (Terraform)
Design solutions for a large-scale multi-tenant architecture (60+ teams, 3 AWS accounts)
Partner closely with data scientists and ML engineers to enable production model deployments
Ensure platform reliability, security, observability,



and cost efficiency Who We’re Looking For Have 4–6 years of experience building production infrastructure for ML or data workloads
Know Databricks or AWS Sage Maker deeply (Databricks experience is strongly preferred)
Are strong in AWS fundamentals (IAM, networking, compute - beyond console clicking)
Can confidently write Python automation and Terraform / IaC without relying on basic syntax searches

Understand the full ML lifecycle: training, versioning, deployment, monitoring

Can design and ship solutions independently, without constant hand‑holding
Have delivered non‑trivial CI/CD pipelines to production
Experience with workflow orchestration and CI/CD tools such as Apache Airflow and Jenkins
Have hands‑on experience with Kubernetes (EKS) Nice To Have Apache Airflow
OAuth / Amazon Cognito, API Gateway
Monitoring tools such as Prometheus, Grafana, New Relic
Cloud cost optimisation experience

Git Ops tooling (FluxCD, ArgoCD) Come and join us! For Poland: In this positio...

📌 Data Intelligence Platform Engineer (Buenos Aires)
🏢 Philip Morris International
📍 Buenos Aires