Senior MLOps Engineer – AI Infrastructure & Pipelines

As a Senior MLOps Engineer – AI Infrastructure & Pipelines, you will automate ML lifecycle processes, build scalable data pipelines, and deploy robust AI systems in production. You will collaborate with data scientists and engineers to develop intelligent automation solutions.

Quick Facts

• Hybrid work model
• Work on AI infrastructure and machine learning pipelines
• Collaborate with data scientists and engineers

Responsibilities

• Design and maintain CI/CD pipelines for machine learning models
• Automate deployment, testing, and monitoring of AI solutions in production environments
• Manage cloud-based infrastructure on AWS, Azure, or GCP and optimize resources for ML workloads
• Collaborate with data scientists to ensure reproducibility and scalability of experiments
• Implement model monitoring and performance tracking systems using tools such as MLflow, Prometheus, or Grafana
• Troubleshoot and resolve production issues promptly to ensure continuous system uptime
• Document workflows, processes, and infrastructure configurations clearly and comprehensively
• Apply best practices for security, compliance, and data governance within AI pipelines
• Support ongoing improvements of MLOps tools, frameworks, and processes
• Stay current with emerging trends and practices in AI infrastructure and MLOps

Requirements

• Minimum 4 years of experience in MLOps, AI Infrastructure, or related engineering fields
• Strong proficiency in Python and scripting languages such as Bash
• Hands-on experience with CI/CD tools such as Jenkins, GitLab CI/CD, or similar
• Knowledge of containerization and orchestration technologies, including Docker and Kubernetes
• Experience with cloud platforms—AWS, Azure, or GCP—for ML and data pipelines
• Familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Deep understanding of data pipelines, ETL processes, and workflow orchestration tools
• Experience with model monitoring and observability tools such as MLflow, Prometheus, or Grafana
• Excellent problem-solving skills and ability to work effectively in cross-functional teams
• Fluent English, written and spoken

Preferred Qualifications

• Kubernetes certification or hands-on experience
• AWS/Azure certification or equivalent
• Knowledge of security and compliance standards relevant to data and AI systems

Language Requirements

• Fluent Polish and English, written and spoken

Eligibility

• Existing legal right to work in the European Union

Application

• Include a CV in English or Polish and a statement confirming consent to the processing and storage of personal data.