Senior ML/AI Engineer – Canadian Tire – Toronto, ON

Canadian Tire Corporation is looking for a Senior ML/AI Engineer to join their team in Toronto, Ontario. This is a hybrid role (four days in-office per week) embedded within one of Canada’s most recognized retail organizations, where you’ll work at the intersection of machine learning, personalization, and large-scale data engineering to shape how offers and recommendations reach millions of loyal customers.

This role goes well beyond model building. You’ll be architecting end-to-end ML platforms, designing agentic AI solutions, and setting the engineering standard for a team working on production-grade recommendation and ranking systems. If you’re energized by owning the full lifecycle — from raw transaction data to deployed model — and want the technical depth and business impact that come with it, this could be the right fit.

About the Role: Senior ML/AI Engineer

As a Senior ML/AI Engineer at Canadian Tire, you’ll develop deep familiarity with the company’s Retail business and Loyalty program, understanding how personalized offers are composed and delivered across retail banners. You’ll design offline evaluation frameworks with rigorous success criteria — ranking metrics, held-out AUC, time-respecting splits, and point-in-time correctness — so that offline improvements reliably translate into real online lift. From matrix factorization and two-tower retrieval to learning-to-rank and sequential architectures, you’ll be selecting and justifying the right modelling approach for each business problem.

On the platform side, you’ll build and optimize large-scale feature engineering in PySpark over hundreds of millions of transaction records, and you’ll design and operate the ML platform layer — feature store, reproducible training pipelines, and cloud training job submission. You’ll also implement agentic AI solutions that automate model improvement under human review, and you’ll mentor engineers and raise the overall engineering bar through code review and documentation.

Benefits and Salary

Canadian Tire offers a broadband salary range of $64,000 to $106,000, with a typical hiring range between $64,000 and $85,000, depending on experience, internal equity, and market conditions. Employees receive comprehensive benefits and retirement programs, performance incentives, continuing education programs, and product discounts. The enhanced flex benefits package includes $5,000 per year in mental health benefits for eligible employees and their families, along with total well-being tools and resources. You’ll also have access to the Triangle Learning Academy, Canadian Tire Profit Sharing, and strong career growth opportunities.

Responsibilities

In this role, you’ll operate across the full ML lifecycle — from raw data to production models — while also contributing to team growth and platform infrastructure. Your work will directly influence how Canadian Tire’s personalization and recommendation systems perform at scale, making technical rigour and business awareness equally important.

• Design and deliver offline evaluation frameworks with clear success criteria including ranking metrics, held-out AUC, time-respecting splits, and point-in-time correctness
• Research and apply modelling methodology — from matrix factorization and two-tower retrieval to learning-to-rank and sequential architectures — selecting the right approach for each business problem
• Build and optimize large-scale feature engineering pipelines in PySpark over hundreds of millions of transaction records
• Design and operate the ML platform layer, including feature store, reproducible training pipelines, and cloud training job submission
• Implement agentic AI solutions that automate model improvement, leveraging an in-house harness where an AI agent proposes, scores, and validates changes under human review
• Lead optimization and orchestration of end-to-end analytical pipelines across multiple data sources and modelling workstreams for production reliability
• Mentor engineers and raise team engineering standards through code review, documentation, and technical guidance
• Develop understanding of the Retail business and Loyalty program to ensure ML solutions align with real business outcomes

Requirements / Skills

The ideal candidate brings a strong quantitative background paired with genuine production ML experience — not just research or prototype work. Canadian Tire values engineers who are equally comfortable in the data layer and the modelling layer, and who can communicate technical decisions clearly to both technical and business stakeholders.

• Education: B.S. or M.S. in Computer Science, Statistics, Math, Engineering, or a related quantitative discipline — PhD is an asset
• 3+ years of experience developing and deploying machine learning solutions in production, including data, training, evaluation, release, and operational support
• Expert-level Python with a focus on writing production-grade ML code (not just notebooks)
• 4+ years querying and analyzing large datasets using SQL and Apache Spark, with demonstrated depth in PySpark
• Recommender systems or large-scale ranking experience, with sound judgement on technique selection
• Deep learning frameworks (PyTorch, TensorFlow) and gradient boosting libraries such as LightGBM or XGBoost
• Cloud ML platform experience — Vertex AI preferred; SageMaker or Azure ML acceptable — including custom training jobs, artifact management, and cost control
• Pipeline orchestration experience, preferably with Apache Airflow at production scale
• Familiarity with agentic AI architectures, LLM-based solutions, and infrastructure-as-code (Terraform) is a strong asset
• Strong written and verbal communication skills with the ability to present both technical and business concepts clearly

How to Apply

To apply, visit the official job posting using the link below. Make sure your resume is up to date and tailored to the role before submitting.

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