1 day ago
Toronto, CanadaSenior

Responsibilities

  • Develop and deploy production machine learning solutions covering data preparation, training, evaluation, release, and operational support.
  • Design offline evaluation frameworks with ranking metrics, held-out AUC, time-respecting splits, point-in-time correctness, and explicit success criteria.
  • Research and apply modeling approaches including matrix factorization, two-tower retrieval, learning-to-rank, and sequential architectures.
  • Build and optimize large-scale feature engineering pipelines in PySpark over hundreds of millions of transaction records.
  • Design and operate ML platform capabilities including a feature store, reproducible training pipelines, and cloud training job submission.
  • Develop agentic AI solutions that propose, evaluate, and retain measurable model improvements under human review.
  • Lead optimization and orchestration of end-to-end analytical pipelines across data sources and modeling workstreams.
  • Raise engineering standards through code review, documentation, and mentorship.

Requirements

  • Bachelor’s or master’s degree in computer science, statistics, mathematics, engineering, or a related quantitative discipline; PhD is an asset.
  • At least 3 years of experience developing and deploying machine learning solutions in production.
  • At least 4 years of experience querying and analyzing large datasets with SQL and Spark, including demonstrated PySpark depth.
  • Expert-level Python and experience writing production-grade machine learning code.
  • Experience with recommender systems or large-scale ranking and with rigorous time-aware, point-in-time-correct offline evaluation.
  • Experience with PyTorch or TensorFlow and gradient boosting libraries such as LightGBM or XGBoost.
  • Production experience with Vertex AI, SageMaker, or Azure ML, including custom training jobs, artifact management, and cost control.
  • Familiarity with BigQuery, cloud-based data structures, Apache Airflow, agentic AI architectures, LLM-based solutions, coding agents, Terraform, and cloud IAM is preferred or an asset.
  • Retail, loyalty program, personalization, or ad-tech ranking experience is preferred.
  • Strong oral and written communication, presentation, independent problem-solving, and ambiguity-navigation skills are required.

Benefits

  • Comprehensive benefits and retirement programs.
  • Performance incentives and continuing education programs.
  • Well-being perks, career growth opportunities, product discounts, and broadband.
  • Hybrid work arrangement in Toronto with four days per week in the office.
  • Additional company programs include learning support, profit sharing, retirement and savings programs, and eligible mental health benefits.

Tech Stack

Apache AirflowApache SparkGoogle BigQueryLightGBMPythonPyTorchSQLTensorFlowTerraformXGBoost

Categories

Canadian Tire Corporation, Limited

About Canadian Tire Corporation, Limited

10,000+ employees

Canadian Tire Corporation is a Canadian retail and financial services group best known for Canadian Tire stores selling automotive, hardware, home, and seasonal goods. It also operates SportChek, Mark’s, PartSource, Party City, and Gas+, owns Helly Hansen, and runs a credit card/loyalty business and CT REIT. Founded in 1922 and headquartered in Toronto, it is publicly traded on the TSX and operates a coast-to-coast dealer and franchise network.

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