Hybrid ML Engineer — Predictive Analytics & NLP (Azure)

Hydro One Limited; Toronto; Hybrid; CAD 90,000 - 140,000; Full time

Job summary

Hydro One Limited in Toronto, Ontario seeks a highly analytical Machine Learning Engineer for a temporary contractor role to design, build, and deploy ML solutions powering predictive analytics, anomaly detection, and operational insights across Hydro One's data ecosystem.

You will work on AMI data-driven models and NLP for ServiceNow analytics, using Azure-based infrastructure to deliver production-ready solutions and clear technical guidelines for maintainability.

Qualifications

• Master's or PhD in Mathematics, Statistics, CS, Data Science, or related field.
• 3+ years experience in ML engineering or data science.
• Proficient in Python, SQL and ML frameworks.
• Experience with Azure ML, MLOps, and CI/CD pipelines.

Responsibilities

• Clean, transform, and manage large datasets.
• Perform feature selection and feature engineering for time-series, clustering, and anomaly detection.
• Design and develop machine learning models (Supervised, Unsupervised, Reinforcement) and deep learning models.
• Build predictive models for metering and network health analyses.
• Apply NLP to ServiceNow analytics and generate thematic insights.
• Run ML tests, train/retrain models to prevent drift and optimize results.
• Document workflows and provide guidelines for maintainability.

Skills

Python

SQL

ML frameworks

Time-series

NLP

Azure ML

MLOps

CI/CD

End-to-end apps

Data cleaning

Feature engineering

Education

Master's or PhD in a quantitative field

Tools

Scikit-learn

XGBoost

TensorFlow

PyTorch

Job description

Hydro One Limited in Toronto, Ontario seeks a highly analytical Machine Learning Engineer for a temporary contractor role to design, build, and deploy ML solutions powering predictive analytics, anomaly detection, and operational insights across Hydro One's data ecosystem.

You will work on AMI data-driven models and NLP for ServiceNow analytics, using Azure-based infrastructure to deliver production-ready solutions and clear technical guidelines for maintainability.