A highly skilled Machine Learning Engineer with 5-10 years of experience in timeseries forecasting sensor level feature engineering and optimization models for industrial energy 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
Years of Experience 5-7 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
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
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Software Engineering Skills
Python NumPy Pandas PyTorch Scikitlearn
PySpark Delta Lake ADLS
REST APIs FastAPIFlask
Git testing frameworks logging monitoring best practices
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Soft Skills
Solid 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
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Work timing 01.30-10.30PM
Skills
Mandatory Skills : MLOPS,AI-ML-NLP-MLOps, Oil Gas industry