Hybrid MLOps Engineer: AI Deployments on Kubernetes
Role details
Job location
Tech stack
Job description
A global consulting firm is seeking an MLOps Specialist to enhance digital capabilities in Madrid, Spain. In this role, you will bridge the gap between Data Science and IT Operations, deploying and maintaining AI applications. You'll work closely with Data Scientists and Product Owners to design robust AI solutions. Candidates should have strong experience with Python, Kubernetes, and CI/CD pipelines. This permanent, full-time hybrid position offers training, development, and comprehensive benefits, including private medical insurance., * Deploy and manage AI applications using Kubernetes.
- Perform ETL processes using Python and Spark.
- Build and maintain APIs for AI/ML solutions.
- Ensure code quality and build deployment pipelines.
- Conduct testing using frameworks such as Pytest.
- Monitor and maintain AI/ML projects in production., Kubernetes Python Spark Git GitHub Actions Sonar Fortify Pytest Control-M Airflow, A global consulting firm is seeking an MLOps Specialist to enhance digital capabilities in Madrid, Spain. In this role, you will bridge the gap between Data Science and IT Operations, deploying and maintaining AI applications. You'll work closely with Data Scientists and Product Owners to design robust AI solutions. Candidates should have strong experience with Python, Kubernetes, and CI/CD pipelines. This permanent, full-time hybrid position offers training, development, and comprehensive benefits, including private medical insurance. Consigue la evaluación confidencial y gratuita de tu currículum
Requirements
Experience implementing AI models using Python Hands-on experience with Kubernetes for deployment Experience performing ETL processes using Python and Spark Experience building and maintaining APIs for AI/ML applications Experience using Git for version control Experience implementing CI/CD pipelines using GitHub Actions Experience with testing frameworks such as Pytest Experience using workflow orchestration tools such as Control-M and Airflow Ability to collaborate with cross-functional teams