MLOps Engineer (Enterprise AI Platform)

Stermedia; Wrocław; Remote; PLN 190,000 - 234,000; Full time

Benefits offered by this job

Flexible hours

Remote work possibility

Self-development budget

Chillout room & events

MultiSport

LuxMed

Job summary

Stermedia is seeking an experienced MLOps Engineer to help build, automate, and scale production-grade AI and ML solutions. You will work at the intersection of ML, cloud engineering, and DevOps to transform models into reliable, scalable services.

Collaborate with data scientists and cloud engineers to deploy, monitor, and maintain ML systems using modern cloud-native tools. The role offers remote work options and a dynamic, tech-forward environment.

Qualifications

• 2+ years in MLOps, DevOps, Cloud Engineering, ML Engineering, or related field.
• Strong Python programming skills (clean, maintainable, testable).
• Docker & Kubernetes: containerization and Kubernetes deployments.
• Cloud Platforms: Azure, AWS, or GCP exposure.
• CI/CD: automated build/test/deploy with GitLab CI or GitHub Actions.
• MLOps Fundamentals: ML workflows, model deployment, experiment tracking.
• Workflow Orchestration: Kubeflow Pipelines, Airflow, or Argo Workflows.
• Infrastructure as Code: Terraform or similar.
• Monitoring: Prometheus, Grafana, or equivalents.
• English: B2+ level for technical discussions and collaboration.

Responsibilities

• Build, automate, and scale production-grade ML solutions.
• Collaborate with Data Scientists, ML Engineers, and Cloud Engineers to deploy and maintain systems.
• Improve model deployment processes and ML infrastructure.
• Monitor, log, and ensure reliability of ML services.

Skills

Python

Docker & Kubernetes

Cloud Platforms

CI/CD pipelines

MLOps Fundamentals

Workflow Orchestration

Infrastructure as Code

Monitoring

English (B2+)

Tools

Kubeflow

Airflow

Argo Workflows

Terraform

Job description

We are looking for an MLOps Engineer to help build, automate, and scale production-grade AI and Machine Learning solutions.

You will work at the intersection of Machine Learning, Cloud Engineering, and DevOps, helping transform ML models into reliable, scalable, and production-ready services.

This role offers the opportunity to work with modern cloud-native technologies, automate ML workflows, improve model deployment processes, and contribute to the development of enterprise AI infrastructure. You will collaborate with Data Scientists, ML Engineers, and Cloud Engineers to ensure that machine learning systems are efficiently deployed, monitored, and maintained.

• 2+ years of hands-on experience in MLOps, DevOps, Cloud Engineering, Machine Learning Engineering, or a related field, including practical exposure to ML deployment or ML workflows.

• Python: Good programming skills, including writing clean, maintainable, and testable code.

• Docker & Kubernetes: Practical experience with containerization and deploying applications in Kubernetes environments.

• Cloud Platforms: Hands-on experience with at least one major cloud provider: Azure, AWS, or GCP.

• CI/CD: Experience with automated build, test, and deployment pipelines using tools such as GitLab CI, GitHub Actions, or similar solutions.

• MLOps Fundamentals: Understanding of ML workflows, model deployment, experiment tracking, and model lifecycle management.

• Workflow Orchestration: Familiarity with at least one orchestration tool, such as Kubeflow Pipelines, Apache Airflow, or Argo Workflows.

• Infrastructure as Code: Practical knowledge of Terraform or similar IaC tools.

• Monitoring: Familiarity with monitoring and logging tools such as Prometheus, Grafana, or equivalent solutions.

• English: B2+ level, sufficient for technical discussions, documentation, and everyday collaboration in an international environment.

Nice to have:

• Experience with MLflow, including experiment tracking and model registry.

• Familiarity with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.

• Experience with model serving technologies such as KServe, NVIDIA Triton Inference Server, vLLM, or ONNX Runtime.

• Knowledge of GitOps and deployment automation using Argo CD or Argo Rollouts.

• Experience with data drift detection, model monitoring, or ML observability tools.

• Familiarity with Apache Kafka, Apache Spark, or distributed data processing.

• Knowledge of GPU-based ML workloads, distributed training, or inference optimization.

• Experience with feature stores (e.g., Feast) or data versioning tools (e.g., DVC).

• Understanding of cloud security, IAM/RBAC, and secrets management.

Salary:

17 000 - 21 000 PLN + VAT (B2B)

We offer you:

• Working with new technologies from the machine learning and top-notch software development area.

• Budget on self-development per year.

• Possibility to contribute to a variety of interesting projects.

• Internal workshops.

• Personal branding (articles, conference speaker, internal workshop leader).

• Flexible work hours.

• Remote work possibility.

• Chillout room / free beverages / team & company events.

• Friendly atmosphere.

• MultiSport.

• LuxMed.