Data Intelligence Platform Engineer

Philip Morris International; Albarraque; Presencial; EUR 60 000 - 90 000; Tempo integral

Resumo da oferta

Philip Morris International is seeking an experienced professional to design and scale a production-grade ML/MLOps platform. You will implement Databricks MLOps, build CI/CD pipelines, and help maintain an AWS SageMaker environment.

You will automate infrastructure with Python and Terraform, support a multi-tenant architecture across AWS accounts, and collaborate with data scientists to enable reliable production model deployments.

Qualificações

• 4–6 years building production infrastructure for ML or data workloads.
• Deep knowledge of Databricks or AWS SageMaker (Databricks preferred).
• Strong AWS fundamentals (IAM, networking, compute).
• Proficient in Python automation and Terraform/IaC.
• Understand the full ML lifecycle: training, versioning, deployment, monitoring.

Responsabilidades

• Design, build, and scale a production-grade ML/MLOps platform.
• Implement Databricks MLOps environments, CI/CD pipelines, and monitoring.
• Maintain and improve the AWS SageMaker ML platform.
• Automate infrastructure and workflows using Python and Terraform.

Conhecimentos

Databricks

AWS SageMaker

Python

Terraform / IaC

CI/CD pipelines

Kubernetes (EKS)

Airflow

Descrição da oferta de emprego

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 SageMaker 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 SageMaker 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 SageMaker 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


• GitOps tooling (FluxCD, ArgoCD)

For Poland: In this position you will earn no less that 17 600 PLN gross monthly

Relocation support is not available for this job

At PMI we run the business in line with ethical principles and encourage SpeakUp culture. We care for equal chances and fair treatment. If you find anything that violates these principles in this job offer or the recruitment process, you may contact our Ethics and Compliance Team at [e-mail]. Read more about Ethics&Compliance at PMI - here.