We are looking for a highly skilled Machine Learning Engineer with 5-7 years of experience in timeseries forecasting, sensor-level feature engineering, and optimization models for industrial energy systems. The ideal candidate will have a strong background working with PI historian operational telemetry and production facility constraints. This position is located in Bangalore.

Roles and Responsibility

- Design end-to-end ML pipelines from OT data extraction and feature engineering to model deployment, monitoring, and operator-centric UI delivery.
- Translate complex ML optimization outputs into clear operational instructions used by field production teams.
- Develop and implement timeseries ML and constrained optimization for production ramp sequence planning.
- Create pressures system feature engineering using DHP, WHP, Manifold, Upstream signals, and comfort reconciling telemetry with physical intuition.
- Handle OThistorian PI data wrangling at scale, including robust handling of gaps, sensor drift, and event slicing for ramp windows.
- Package Azure ML models, endpoints, and monitoring, as well as hands-on CICD for retrains and migrating HPC-trained models to cloud-served artifacts.
- Deliver operator-centric solutions, translating model outputs into transparent ramp steps, visual cues, stoplights, and validating against control room practice.





Job Requirements

- Strong cross-functional communication skills with production engineers, operators, and SMEs.
- High ownership and ability to simplify complex ML outputs.
- Comfortable working with ambiguity and evolving requirements.
- Ability to lead design discussions and technical decisions.
- Proficient in designing end-to-end ML pipelines from OT data extraction and feature engineering to model deployment, monitoring, and operator-centric UI delivery.
- Experience in oil gas energy or industrial automation environments.
- Exposure to artificial lift systems (ESP), gas lift, or hydraulic flow models.
- Knowledge of physics-based modeling, surrogate modeling, or hybrid ML/physics workflows.
- Experience with real-time streaming using Event Hubs, Kafka, and IoT Hub.
- Software Engineering Skills: Python, NumPy, Pandas, PyTorch, Scikit-Learn, PySpark Delta Lake ADLS, REST APIs (FastAPI/Flask).
- Git testing frameworks and logging monitoring best practices.
- Work timing: 01:30 PM - 10:30 PM.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Specialist - Architecture (Karnataka)
🏢 LTM
📍 Karnataka