**Job Brief:** We are looking for an experienced **ML Ops Engineer** with 10 years of experience in deploying and managing machine learning models within digital oilfield environments. This remote opportunity is with **one of our esteemed clients**, offering the chance to work on cutting\-edge data infrastructure and automation systems that drive next\-generation energy analytics. **Key Responsibilities:** * Design and implement scalable ML pipelines for digital oilfield data processing and automation. * Develop and maintain CI/CD frameworks for model training, validation, and deployment. * Collaborate with data scientists and domain experts to ensure reliable, production\-grade model operations. * Manage and monitor ML models using tools such as MLflow, Kubeflow, or Airflow. * Implement best practices for data versioning, containerization (Docker), and orchestration (Kubernetes). * Ensure compliance with data governance, security, and performance standards. * Drive automation and performance optimization across the entire ML lifecycle. **Required Qualification / Experience / Skills:** * Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. * Minimum 10 years of experience in ML Ops or data engineering, preferably within the oil \& gas sector. * Expertise in Python, Linux, Docker, and Kubernetes. * Strong understanding of CI/CD tools (GitLab CI, Jenkins) and cloud environments (AWS, Azure). * Proven experience deploying ML models in production for real\-time analytics. * Familiarity with time\-series data, IoT systems, and SCADA integration. * Excellent communication, documentation, and troubleshooting skills. **Job Location: Remote** **Type of Employment: Permanent / Full time** **Salary: Negotiable (based on experience)** **What you can expect from the employer:** * Competitive compensation based on experience. * Exposure to digital transformation projects in the energy industry. * Remote work flexibility and supportive work environment. * Continuous learning and career advancement opportunities. Job Types: Full\-time, Permanent Application Question(s): * Do you have experience in ML Ops frameworks and deployment pipelines? * Have you worked in digital oilfield or industrial automation environments? * Are you experienced with Docker, Kubernetes, and cloud\-based ML systems? * Do you have 10 years of relevant experience in ML Ops or related fields?