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Machine Learning Engineer - Canada

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Job Description - Machine Learning Engineer - Canada


Machine Learning Engineers help deliver machine learning solutions for industrial process environments: fault detection, predictive maintenance, quality optimization, and process control. You’ll work across the full project lifecycle: scoping problems with plant engineers, wrangling messy sensor data, building and deploying models, and making sure they work in production. 

Machine Learning Engineers demonstrate:

  • High integrity
  • A willingness to go beyond the ordinary to meet and exceed client expectations
  • A desire for continual challenge and development, and excellent written and verbal communication skills

Reports To: Machine Learning Lead

JOB QUALIFICATIONS

Roles and responsibilities for this job may include, but are not limited to:

  • Develop and deploy ML models (classification, regression, anomaly detection, time-series forecasting) for industrial process applications 
  • Collaborate with process engineers and operators to translate domain problems into well-scoped ML tasks 
  • Build robust data pipelines from historians, SCADA systems, and other industrial data sources 
  • ​​​​​​​Design feature engineering strategies grounded in physical process understanding 
  • ​​​​​​​Validate models against real plant conditions, not just offline metrics 
  • ​​​​​​​Containerize and deploy models using Docker, with experience in Kubernetes or similar orchestration tools 
  • ​​​​​​​Support model monitoring, retraining workflows, and CI/CD for ML pipelines
  • ​​​​​​​Require domestic and international travel

Required Experience

  • Degree in Engineering (Electrical, Mechanical, Chemical, or similar), Computer Science, or similar scientific/technical field
Pay Range

​​​​​​​This position pays 120k and 180K CAD. 
 

Ideal Experience

  • 3-5 years of experience in applied ML or data science, ideally in manufacturing, process industries, or adjacent fields 
  • Strong Python skills: scikit-learn, pandas, NumPy as a baseline 
  • ​​​​​​​Experience with a range of ML approaches: gradient boosting (LightGBM, XGBoost), deep learning frameworks (PyTorch or TensorFlow), and unsupervised methods (clustering, autoencoders, anomaly detection) 
  • ​​​​​​​Familiarity with time-series data and the challenges that come with it (irregular sampling, sensor drift, missing data, class imbalance) 
  • ​​​​​​​Working understanding of process engineering fundamentals: heat/mass balance, process flow diagrams, and common unit operations 
  • ​​​​​​​Practical experience with Docker; familiarity with Kubernetes, Helm, or cloud container services 
  • ​​​​​​​Comfort working with messy, real-world data rather than clean benchmark datasets 
  • ​​​​​​​Ability to communicate model results and limitations clearly to non-ML stakeholders 
  • ​​​​​​​Must be eligible to work in the United States and Canada or able to obtain appropriate work authorization (visa sponsorship may be available) 
  • ​​​​​​​Ability to travel domestically and internationally, including to industrial and manufacturing facilities 
Highly Valued Experience
  • Experience with process control systems (DCS/PLC), control loop tuning, SCADA, and MES systems 
  • ​​​​​​​Familiarity with OPC-UA, MQTT, PI Historian, or similar industrial data infrastructure 
  • Exposure to Bayesian methods or probabilistic modeling 
  • Experience with MLOps tooling (MLflow, Kubeflow, Airflow, or similar) 
  • Experience deploying models in edge, on-premise, and cloud environments 
  • Background in controls, chemical, mechanical, or process engineering 
Original job Machine Learning Engineer - Canada posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
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About the Company

Logical Systems

LSI is an outcome-driven automation and controls systems integrator. We start every project by listening, and are eager to hear about yours.

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