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MLOps Engineer (Energy) - MLEEAS - Responsibilities
MLOps Engineer
Senior MLOps Engineer to build and automate ML deployment pipelines, implement CI/CD for ML systems, and monitor model performance in energy applications.
About the role
Key the organization
- Design and implement robust ML deployment pipelines for energy systems
- Develop and maintain CI/CD workflows tailored for machine learning models
- Automate model retraining and validation processes to ensure up-to-date performance
- Monitor model performance metrics and detect data drift in real-time
- Collaborate with data scientists and software engineers to optimize ML system reliability
- Implement best practices for model versioning, testing, and rollback strategies
Requirements
- 3+ years of experience in MLOps, DevOps, or related fields
- Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch)
- Experience with CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI)
- Knowledge of cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes)
- Strong understanding of model monitoring, logging, and alerting systems
Skills
mlopsci cdmachine learningpython