Machine Learning Engineer – Digital Oilfield Systems

Confidential Company

Role Overview:

We are hiring a Machine Learning Engineer to support the development and deployment of Digital Oilfield analytics and optimization solutions. The role focuses on using AI/ML techniques to enhance production efficiency, predictive maintenance, and real-time decision support across upstream oilfield systems.

Key Responsibilities:

• Develop and deploy ML models for production forecasting, downtime prediction, and well performance optimization.

• Build pipelines to process and analyze real-time sensor data (pressure, temperature, flow) from wells and surface facilities.

• Design and implement data-driven anomaly detection models to identify potential failures in well and pipeline systems.

• Collaborate with petroleum and production engineers to translate business challenges into ML-based workflows.

• Build ML APIs, integrate models with visualization dashboards (e.g., Power BI, Grafana), and enable continuous learning systems.

• Automate data collection and feature engineering from PI, SCADA, and historian systems.

• Apply time series analysis, regression, and classification methods for operational prediction.

• Implement scalable ML pipelines using cloud-based or containerized infrastructure (Azure/AWS preferred).

• Ensure data governance, model validation, and quality assurance before deployment.