Job description:

Job Description
Years of Experience: 5-10years,
Work timing - 01:30 -10:30 PM shifts
Preferable: Production Engineering knowledge Oil & Gas industry
Timeseries ML and constrained optimization for production ramp/sequence planning; ability to encode facility guardrails and drawdown targets.
Pressure system feature engineering using DHP/WHP/Manifold/Up/Downstream signals; comfort reconciling telemetry with physical intuition.
OT/historian (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 CI/CD for retrains and can migrate from HPCtrained models to cloudserved artifacts.
Operatorcentric delivery: translating model outputs into clear ramp steps/visual cues (stoplights, countdowns) and validating against controlroom practice.
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Profile Requirement :
A highly skilled Machine Learning Engineer with 5–10 years of experience in timeseries forecasting, sensorlevel 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 pipelines—from OT data extraction and feature engineering to model deployment, monitoring, and operatorcentric UI delivery. Adept at translating complex ML/optimization outputs into explicit operational instructions used by field/production teams.
Senior ML Engineer (6+ years)
Applied Scientist – Energy Optimization
OT Data + ML Specialist
Azure ML: Pipelines, endpoints, environments, registries
ADF and Azure Databricks (PySpark, Delta Lake, DLT)
CI/CD 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 (FastAPI/Flask).
? Preferred Qualifications
Experience in oil & gas, energy, or industrial

📌 DATA SCIENTIST LEAD (Hyderabad)
🏢 Wipro
📍 Hyderabad