DevOps Engineer AI/ML

Experis is a global leader in recruitment of IT specialists and management staff in key IT areas. It offers competitive employment opportunities and interesting IT projects for both experienced experts and newcomers to the IT industry. Experis is part of ManpowerGroup and has been recognized as one of the most ethical companies in the world.

• Strong experience with DevOps tools such as Jenkins, GitHub Actions, Kubernetes, Docker, and Terraform
• Solid understanding of major cloud platforms including AWS, Azure, and Google Cloud, along with their AI and ML services
• Experience with AI oriented pipeline and workflow tools such as MLflow, Kubeflow, or Airflow
• Proficiency in scripting and programming languages including Python, Bash, and YAML
• Ability to implement automated testing frameworks for AI models and workflows
• Experience designing secure environments for AI driven systems
• Hands on experience with AI powered monitoring and diagnostics tools such as AIOps platforms or Grafana with ML extensions
• Bachelor’s degree in Engineering, IT, Science, or a related technical field
• Minimum 5 years of experience in a corporate IT environment in a similar role
• Strong communication skills and ability to collaborate with international teams

Nice to have:

• DevOps or AI/ML certifications such as Kubernetes or AWS Machine Learning Specialty
• Experience working with AIOps platforms to improve operational efficiency
• Knowledge of specialized data pipeline automation tools for machine learning use cases
• Hands on experience with AI and ML frameworks including TensorFlow, PyTorch, or Scikit learn in production environments

• Design and maintain CI/CD pipelines integrating AI and ML tools and frameworks
• Collaborate with AI teams to deploy and scale machine learning models in production environments
• Integrate AI-based monitoring, alerting, and analytics solutions to enhance pipeline visibility and enable predictive insights
• Optimize infrastructure and resource utilization for AI workloads across cloud, on premises, and hybrid environments
• Ensure strong security practices within AI driven pipeline ecosystems
• Troubleshoot pipeline and infrastructure issues, particularly those related to AI components, ensuring high availability
• Monitor system performance and implement continuous improvements using AI enhanced tools

Location: 100% remote work (Poland)