Job Description
Project Description:
We are hiring an ML Ops Engineer to operationalize machine learning solutions across Digital Oilfield (DOF) platforms. This is a critical role ensuring that models move from development to robust, production-grade deployment with high availability, traceability, and security.
The ideal candidate will be responsible for automating pipelines, managing model versions, integrating APIs, and monitoring ML system health across diverse operational environments. Oil & gas exposure is beneficial but not required; this is a technical engineering role with high ownership and cross-team collaboration.
Responsibilities:
• Develop and maintain ML pipelines for data preprocessing, training, validation, deployment, and monitoring.
• Implement model governance strategies—versioning, rollback, audit trails, and explainability.
• Set up containerized environments and scalable inference systems (e.g., using Docker, Kubernetes).
• Collaborate with software, IT, and...
We are hiring an ML Ops Engineer to operationalize machine learning solutions across Digital Oilfield (DOF) platforms. This is a critical role ensuring that models move from development to robust, production-grade deployment with high availability, traceability, and security.
The ideal candidate will be responsible for automating pipelines, managing model versions, integrating APIs, and monitoring ML system health across diverse operational environments. Oil & gas exposure is beneficial but not required; this is a technical engineering role with high ownership and cross-team collaboration.
Responsibilities:
• Develop and maintain ML pipelines for data preprocessing, training, validation, deployment, and monitoring.
• Implement model governance strategies—versioning, rollback, audit trails, and explainability.
• Set up containerized environments and scalable inference systems (e.g., using Docker, Kubernetes).
• Collaborate with software, IT, and...
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