ML Engineer

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

This is a temporary contractor position.

Job Overview

We are seeking a highly analytical and technically proficient Machine Learning Engineer to design, build, and deploy ML solutions that power predictive analytics, anomaly detection, and operational insights across Hydro One's data ecosystem. This role is ideal for someone with a strong foundation in mathematics, statistics, and programming, and a passion for applying AI/ML to solve complex operational challenges.

You will work on AMI data-driven models, NLP for ServiceNow analytics, and network reliability forecasting, leveraging Azure-based infrastructure for scalable deployments and many other high-impact data science projects driving operational efficiency and customer experience improvements.

What You Will Do

• Clean, transform, and manage large structured, semi-structured, and unstructured datasets.
• Perform feature selection and feature engineering for time-series, clustering, and anomaly detection.
• Design and develop machine learning models (Supervised, Unsupervised, and Reinforcement Learning) and deep learning models (e.g., Neural Networks, autoencoders).
• Build predictive models for overloaded/underloaded metering detection, temperature anomaly monitoring, equipment replacement forecasting, and network health analysis etc.
• Apply NLP techniques to categorize and interpret ServiceNow inquiries, identify recurring issues, and generate thematic insights.

Testing & Optimization

• Run ML tests and experiments, train and retrain systems to prevent drift and optimize results.
• Implement evaluation metrics, monitor performance, and ensure models meet quality and compliance standards.

Advanced Analytics & Insights

• Conduct large-scale analysis to discover patterns and trends using statistical and ML techniques.
• Perform regression, attribution modeling, variable importance analysis, and causality studies.
• Work closely with data engineers, ML engineers, and business partners to deliver production-ready solutions.
• Document workflows and provide clear technical guidelines for maintainability.

Required Qualifications

• Master's or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, or related field.
• 3+ years? experience in ML engineering or data science roles.
• Strong proficiency in Python, SQL, and ML frameworks (Scikit-learn, XGBoost, TensorFlow, PyTorch).
• Hands-on experience with feature engineering, feature selection, and data cleaning.
• Expertise in time-series modeling, anomaly detection, and predictive maintenance.
• Experience with NLP techniques for text classification and sentiment analysis.
• Familiarity with Azure Machine Learning, MLOps, and CI/CD pipelines.
• Having experience of building end-to-end applications in production.
• Nice to have Knowledge of AMI systems, utility data models, and ServiceNow analytics.

Preferred Skills

• Strong problem-solving mindset with ability to debug, optimize, and deliver robust solutions.
• Excellent communication skills to explain complex models to non-technical stakeholders.

This is a hybrid role requiring the contractor to be on site at least 2 days per week at the Hydro One office in Toronto, ON.