ML Platform Engineer - Databricks & SageMaker at Scale

Philip Morris International; Albarraque; Presencial; EUR 41 000 - 50 000; Tempo integral

Resumo da oferta

Philip Morris International in Poland is seeking a production-grade ML platform engineer to design, build, and scale an MLOps platform used by 300+ data scientists and ML engineers across multiple teams. You will standardize Databricks MLOps environments, CI/CD pipelines, and model monitoring, and contribute to AWS SageMaker platform evolution.

You will automate infrastructure with Python and Terraform, design multi-tenant architecture for 60+ teams across three AWS accounts, and partner with

Qualificações

• 4–6 years of experience building production infrastructure for ML or data workloads.
• Deep knowledge of Databricks or AWS SageMaker (Databricks preferred).
• AWS fundamentals (IAM, networking, compute) beyond basic tooling.
• Proficient in Python automation and IaC (Terraform) without simple searches.
• Understanding of 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, monitoring).
• Maintain and improve the AWS SageMaker ML platform.
• Automate infrastructure and workflows using Python and Terraform.
• Design solutions for a large-scale multi-tenant architecture (60+ teams, 3 AWS accounts).
• Collaborate with data scientists and ML engineers to enable production deployments.
• Ensure platform reliability, security, observability, and cost efficiency.

Conhecimentos

Databricks

AWS SageMaker

Python automation

Terraform / IaC

Kubernetes (EKS)

CI/CD pipelines

Apache Airflow

Jenkins

Multi-tenant architecture

Cloud cost optimisation

Ferramentas

Terraform

Apache Airflow

Jenkins

Kubernetes (EKS)

Descrição da oferta de emprego

Philip Morris International in Poland is seeking a production-grade ML platform engineer to design, build, and scale an MLOps platform used by 300+ data scientists and ML engineers across multiple teams. You will standardize Databricks MLOps environments, CI/CD pipelines, and model monitoring, and contribute to AWS SageMaker platform evolution.

You will automate infrastructure with Python and Terraform, design multi-tenant architecture for 60+ teams across three AWS accounts, and partner with