As discussed, PFB details and enable 5 profiles at the earliest by before 6 PM

Summary:

- Years of Experience: 6-12years
- Work timing - 01:30 -10:30 PM
- Location - Bangalore
- Notice Period - 0-30 days
- Budget: Max 22 LPA (Pls be within this range)
- 1st Round - Virtual
- Final round - Face to Face at client location at Bellandur, Bangalore
- F2F Location - 32 RMZ Ecoworld, Bellandur, Bangalore
- Ready to work from client location (4 days WFO) and every Monday WFH.

Description:

- 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).

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; hands on with CI/CD for retrains and can migrate from HPC trained models to cloud served artifacts.

Operator centric delivery: translating model outputs into clear ramp steps/visual cues (stoplights, countdowns) and validating against control room practice.

Key Responsibilities:

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. Solid background working with PI historian, operational telemetry, and production facility constraints. Proficient in designing end to end ML pipelines-from OT data extraction and feature engineering to model deployment, monitoring, and operator centric UI delivery. Adept at translating complex ML/optimization outputs into clear operational instructions used by field/production teams.

Must Have Skills

- PySpark
- NumPy
- RESTAPI

Good to have Skills

- Azure Data Lake

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.

📌 Sr ML Engineer -Chevron-HCL-Ritu Rajarshi Ghosh (Bengaluru)
🏢 PSRTEK
📍 Bengaluru