Senior ML Platform Engineer – Scalable MLOps & Pipelines

Philip Morris International; Kraków; On-site; PLN 179,000 - 214,000; Full time

Job summary

Philip Morris International Kraków is seeking an experienced ML/MLOps Platform Engineer to design and scale a production‑grade ML platform used by 300+ data scientists across 60+ teams. You’ll focus on Databricks MLOps and AWS SageMaker, ensuring deployments are reliable, secure, and scalable.

Work with data scientists to automate infrastructure with Python and Terraform, design multi‑tenant solutions for 60+ teams across AWS accounts, and drive cost efficiency, observability, and security at

Qualifications

• 4–6 years of production ML/data infra experience.
• Deep knowledge of Databricks or AWS SageMaker.
• Strong AWS fundamentals (IAM, networking, compute).
• Proficient Python automation and IaC (Terraform).
• Understanding ML lifecycle: training, versioning, deployment, monitoring.
• Ability to design and ship CI/CD pipelines to production.
• Experience with Airflow and Jenkins.
• Hands-on Kubernetes (EKS) experience.

Responsibilities

• Design, build, and scale production-grade ML/MLOps platform.
• Implement Databricks MLOps (environments, CI/CD, monitoring).
• Maintain and improve AWS SageMaker platform.
• Automate infra using Python and Terraform.
• Design multi-tenant architecture for 60+ teams across 3 AWS accounts.
• Collaborate with data scientists to enable production deployments.
• Ensure reliability, security, observability, and cost efficiency.

Skills

Databricks

AWS SageMaker

Python automation

Terraform / IaC

CI/CD pipelines

Kubernetes (EKS)

Apache Airflow

AWS fundamentals

ML lifecycle

Security IAM

Tools

Terraform

Kubernetes (EKS)

Apache Airflow

Job description

Philip Morris International Kraków is seeking an experienced ML/MLOps Platform Engineer to design and scale a production‑grade ML platform used by 300+ data scientists across 60+ teams. You’ll focus on Databricks MLOps and AWS SageMaker, ensuring deployments are reliable, secure, and scalable.

Work with data scientists to automate infrastructure with Python and Terraform, design multi‑tenant solutions for 60+ teams across AWS accounts, and drive cost efficiency, observability, and security at