Specialist - Architecture

Location- Bangalore Years of Experience 3-5 years Preferable Production Engineering knowledge Oil Gas industry Timeseries ML and constrained optimization for production rampsequence planning ability to encode facility guardrails and drawdown targets Pressuresystem feature engineering using DHPWHPManifoldUpDownstream signals comfort reconciling telemetry with physical intuition OThistorian PI data wrangling at scale robust handling of gaps sensor drift and event slicing for ramp windows Azure ML model packaging endpoints monitoring handson with CICD for retrains and can migrate from HPCtrained models to cloudserved artifacts Operatorcentric delivery translating model outputs into clear ramp stepsvisual cues stoplights countdowns and validating against controlroom practice Profile Requirement A highly skilled Machine Learning Engineer with 5-10 years of experience in timeseries forecasting sensorlevel feature engineering and optimization models for industrialenergy systems Strong background working with PI historian operational telemetry and production facility constraints Proficient in designing endtoend ML pipelinesfrom OT data extraction and feature engineering to model deployment monitoring and operatorcentric UI delivery Adept at translating complex MLoptimization outputs into clear operational instructions used by fieldproduction teams Senior ML Engineer 3 years Applied Scientist Energy Optimization OT Data ML Specialist Azure ML Pipelines endpoints environments registries ADF and Azure Databricks PySpark Delta Lake DLT CICD via Azure DevOps YAML pipelines automated retrains Monitoring Application Insights Azure Monitor data drift monitors Containerization Docker ONNX model packaging Working knowledge of containerization Docker and API deployment FastAPIFlask Preferred Qualifications Experience in oil gas energy or industrial automation environments Exposure to artificial lift systems ESPgaslift or hydraulic flow models Knowledge of physicsbased modeling surrogate modeling or hybrid MLphysics workflows Experience with realtime streaming Event Hubs Kafka IoT Hub Shape Software Engineering Skills Python NumPy Pandas PyTorch Scikitlearn PySpark Delta Lake ADLS REST APIs FastAPIFlask Git testing frameworks logging monitoring best practices Shape Soft Skills Strong crossfunctional communication with production engineers operators SMEs High ownership ability to simplify complex ML outputs Can work with ambiguity and evolving requirements Comfortable leading design discussions and technical decisions Shape Work timing 01.30-10.30PM 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.