Artificial Intelligence/Machine Learning Engineer (6-12 yrs)

Key Responsibilities :

AI/ML Development :

- Design, develop, and deploy AI/ML models (e.g., PINNs, RNNs, Gradient Boosting) to simulate, predict, and optimize drilling fluid performance.

- Develop real-time anomaly detection systems for sensor data from drilling operations.

- Implement time-series analysis models for monitoring and forecasting drilling fluid properties.

Data Management :

- Integrate and manage large-scale data from various sources (sensors, lab results, historical data) into Azure Data Lake or Synapse Analytics.

- Perform data cleaning, preprocessing, and exploratory analysis to identify actionable insights.

Cloud Integration :

- Deploy and scale AI solutions using Azure Machine Learning, Azure Kubernetes Service (AKS), and Azure Stream Analytics.

- Build and automate workflows using Azure Logic Apps and IoT Hub for seamless integration with drilling systems.

- Work closely with cross-functional teams, including drilling engineers, data scientists, and IT specialists, to understand requirements and deliver tailored solutions.

- Provide detailed reporting and visualization using Power BI to communicate results and insights effectively.

- Monitor AI model performance using Azure Monitor and incorporate feedback to refine and improve predictions.

- Stay updated with the latest trends in AI/ML and cloud technologies to implement innovative solutions.

- 6+ years of experience in AI/ML development, with at least 2 years in the oil and gas industry or related fields.

- Strong background in predictive modeling, simulation, and optimization of fluid systems.

- Proficiency in Python, TensorFlow, PyTorch, and scikit-learn for AI/ML model development.

- Expertise in Azure services, including Azure Machine Learning, Data Lake, Synapse Analytics, and IoT Hub.

- Familiarity with time-series analysis tools (RNNs, LSTMs) and physics-informed modeling (PINNs).