Job Title : Senior Machine Learning Engineer (MLOps | Industrial AI | Oil & Gas)

Location : Bengaluru

Work Timings : 1 : 30 PM 10 : 30 PM

Experience : 57 Years (Oil & Gas / Production Engineering experience preferred)

Key Responsibilities :

- Develop time-series ML models and constrained optimization solutions for production ramp sequence planning.

- Build robust feature engineering pipelines using DHP, WHP, manifold, upstream/downstream pressure signals.

- Work with OT Historian / PI System data, handling telemetry gaps, sensor drift, and event-based data slicing.

- Design and deploy scalable ML solutions using Azure Machine Learning, including model packaging, endpoints, monitoring, and CI/CD pipelines.

- Translate ML predictions into operator-friendly workflows with clear visual cues, ramp recommendations, and control-room validation.

- Collaborate with production engineers, operators, and domain SMEs to deliver impactful AI solutions.

Required Skills :

1. Mandatory :

- MLOps

- Python, NumPy, Pandas

- PyTorch, Scikit-learn

- Azure Machine Learning

- Azure DevOps CI/CD

- Docker

- REST APIs (FastAPI/Flask)

- Git and software engineering best practices

Technical Expertise :

- Time-series forecasting and sensor-level feature engineering

- Production optimization for industrial/energy systems

- PI Historian and operational telemetry

- Azure ML Pipelines, Endpoints, Environments & Registries

- Azure Data Factory (ADF)

- Azure Databricks, PySpark, Delta Lake & DLT

- ONNX model packaging

- Azure Monitor & Application Insights

- Data drift monitoring and automated model retraining

Preferred Qualifications :

- Experience in Oil & Gas, Energy, or Industrial Automation

- Knowledge of Production Engineering

- Exposure to Artificial Lift Systems (ESP/Gas Lift) or hydraulic flow models

- Experience with Physics-informed ML, surrogate modeling, or hybrid AI models

- Hands-on with Kafka, Azure Event Hubs, or IoT Hub