Orcapod Consulting Services
Machine Learning Engineer
Skills
2 months ago
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Important information
Contract type:
Permanent
Salary:
₹1,500,000 – ₹2,750,000 / year
Location:
Bengaluru, Karnataka, India
Work mode:
Hybrid
Published on:
17 August 2026
What they need
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
Skills
Mandatory Skills : MLOPS,Time Series Machine LearningAzure Machine Learning, MLOps & CI/CD, Data Engineering (ADF, Databricks, PySpark),Python & Machine Learning Frameworks,Model Deployment & APIs, Monitoring, Drift Detection & Observability
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