Must have

• DevOps

• Terraform

• Python

• Kubernetes

• GitLab

• AWS

• MLOps

• MLflow

• Kubeflow

• Cloud

• Docker

• AWS CDK

• English

• Polish

Nice to have

• YAML

• Security

• Audits

• Grafana

• Datadog

Requirements description

Must-Have Skills

• 4+ years of experience in MLOps / DevOps / ML Engineering
• Strong Python and cloud experience (preferably AWS)
• Hands-on with Docker, Kubernetes, GitLab CI, and Terraform/CDK
• Familiar with ML model pipelines, monitoring, and deployment
• Comfortable working in cross-functional agile teams

Nice to Have

• Knowledge of MLflow, Kubeflow, KServe or SageMaker
• Experience with FinOps, cloud budgeting, or security audits
• Familiarity with Grafana, Datadog or other observability stacks
• Background in Life Sciences or regulated environments

Your responsibilities

1. Support design and implementation of MLOps infrastructure and CI/CD workflows
2. Contribute to cloud architecture and automation (IaC, containerization, monitoring)
3. Help with PoCs and evaluations of new tools
4. Collaborate with teams on task planning and technical decision-making
5. Take part in security, compliance, and cost optimization processes
6. Ensure documentation and smooth collaboration with data science and platform teams