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Added 5 mins ago
TU
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Canadian Tire Corporation

Senior ML/AI Engineer, Advanced Analytics & Modelling - Customer Intelligence Platforms

Toronto, ON, Canada

Broadband Salary Range: $64,000 – $106,000. · Full-time

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Job details

Pay: Broadband Salary Range: $64,000 – $106,000.
Job type: Full-time
Apply by: Nov 18, 2026
Experience: 5+ years developing, deploying and supporting ML or AI solutions in production, including meaningful hands-on experience with production GenAI systems.
Posting language: English
Posted: Nov 4, 2026

Original job description

What You'll Do:

We are seeking a highly technical and hands-on ML/AI Engineer to take end-to-end ownership of one of CTC's strategic customer intelligence platforms. The platform combines machine learning, generative AI and large-scale transaction data to identify customer shopping missions and behavioural patterns across hundreds of millions of transactions. Its outputs support Personalization, marketing, merchandising, dealer and broader customer analytics use cases.

The successful candidate will lead the transition of the third party-developed engine into a fully owned CTC capability. This includes mastering the existing code, prompts, models, data pipelines and architecture; operating and improving the production engine; and determining where components should be tuned, refactored or rebuilt. The individual will be the technical authority for the platform across CTC and the primary partner to teams that depend on its outputs.

Lead the technical transition of the platform and underlying models, ensuring full understanding of the code, documentation, environments, operating knowledge and controls required to own the platform independently.

Develop a deep understanding of the full engine, including customer occasion discovery and catalogue generation, transaction tagging, feature engineering, model inference, data flows and downstream outputs.

Run the production platform end-to-end, including scheduled scoring and catalogue refreshes, model and prompt releases, pipeline monitoring, incident investigation and root-cause remediation.

Own the platform's ML capabilities, including transaction classification, clustering, feature development, model validation, performance monitoring, and drift management.

Own its GenAI capabilities, including prompt architecture, context construction, model selection, prompt and model tuning, structured outputs and catalogue-generation workflows.

Build rigorous ML and GenAI evaluation frameworks using representative test sets, automated measures, human review, regression testing and analysis of failure modes.

Implement production controls for GenAI, including guardrails, validation, confidence thresholds, fallback logic, version traceability and monitoring of quality, latency, usage and cost.

Write and maintain production-grade Python and PySpark code across large-scale data processing, feature engineering, model execution, testing and deployment.

Support Personalization and other enterprise use cases, translating requirements into platform enhancements and resolving model, data, integration and production issues.

Improve the platform's accuracy, reliability, scalability, maintainability, runtime, and cost efficiency while ensuring continuity for downstream users.

Assess the current architecture objectively and lead the refactoring, redesign or rebuilding of components that do not meet CTC's long-term needs.

Establish strong software engineering, MLOps and LLMOps practices, including automated testing, deployment, rollback, observability, and technical documentation.

What You Bring:

Graduate-level education in Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering or related technical discipline.

5+ years developing, deploying and supporting ML or AI solutions in production, including meaningful hands-on experience with production GenAI systems.

Advanced Python, SQL, PySpark and Spark skills, with experience building maintainable, tested and production-grade software rather than analytical notebooks alone.

Strong foundation in supervised and unsupervised learning, including classification, clustering, feature engineering, model validation, monitoring, and drift detection.

Hands-on production prompt engineering experience, including prompt design, context construction, structured outputs, versioning, regression testing and optimization.

Experience selecting, evaluating and tuning foundation LLMs, with a clear understanding of when to use prompt engineering, retrieval, model adaptation or fine-tuning.

Experience evaluating GenAI systems through representative test sets, automated and human review, quality measures, structured error analysis, and production monitoring.

Experience implementing GenAI controls, including grounding, guardrails, validation, fallback strategies, observability and model and prompt lineage.

Experience with Azure and Databricks, including MLflow, Azure Data Lake Storage, Azure Data Factory, Synapse and related data and deployment services.

Experience with CI/CD, automated testing, version control, containerization, and release management for ML and GenAI applications.

Strong problem-solving and root-cause analysis skills, with the ability to explain model behaviour, limitations and technical trade-offs to technical and non-technical partners.

Experience with customer intelligence, recommendation systems, and behavioral modelling is an asset.

Experience with large-scale batch inference, retrieval-augmented generation, semantic search, vector databases or agentic workflows is an asset.

Experience in retail, loyalty, marketing, ecommerce, or customer analytics is an asset.

Location: Toronto, Ontario (Hybrid: In-office 4 days per week)

We’re always looking for great talent! In addition to competitive pay, we offer:

Comprehensive benefits and retirement programs
Performance incentives, Continuing Education Programs
Other perks to support your well-being
Career growth opportunities and product discounts

Broadband Salary Range: $64,000 – $106,000.
Salary decisions are also dependent on other factors such as your experience, industry benchmarks, internal equity and other role-specific requirements. For critical roles, the compensation offering will be reviewed to ensure alignment with market rate and conditions and the unique value you bring to the role.

We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters.

About Us

Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, over 1,600 retail locations, financial services, exemplary e-commerce capabilities, and exciting market-leading merchandising strategies. We dream big and work as one to innovate with purpose for our customers at every level of our business, investing in new technologies and products, and doubling down on top talent to drive the company forward. We offer competitive salaries and wages to CTC employees, as well as store discounts, supported learning through our Triangle Learning Academy, Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees. As part of our enhanced flex benefits program, we offer mental health benefits in the amount of $5,000 per year for benefits-eligible employees and their families, including total well-being, and mental health tools and resources for all employees. Join us in helping to make life in Canada better through living and working our Core Values: we are innovators and entrepreneurs at our core, outcomes drive us, inclusion is a must, we are stronger together and we take personal responsibility. It is an especially exciting time to join CTC and its family of companies where career opportunities are wide-ranging! Join us, where there's a place for you here.

Our Commitment to Diversity, Inclusion and Belonging

We are committed to fostering an environment where belonging thrives, and diversity, inclusion and equity are infused into everything we do. We believe in building an organizational culture where people are consistently treated with dignity while respecting individual religion, nationality, gender, race, age, perceived ability, spoken language, sexual orientation, and identification. We are united in our purpose of being here to help make life in Canada better.

Accommodations

We stand firm in our Core Value that inclusion is a must. We welcome and encourage candidates from equity-seeking groups such as people who identify as racialized, Indigenous, 2SLGBTQIA+, women, people with disabilities, and beyond. Should you require any accommodation in applying for this role, or throughout the interview process, please make them known when contacted and we will work with you to help meet your needs.

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More about this job

Responsibilities

The engineer will lead the technical transition and ownership of a strategic customer intelligence platform, managing its end-to-end production operations. Responsibilities include developing ML and GenAI capabilities, optimizing data pipelines, and ensuring the platform's scalability and reliability.

Requirements

Candidates must have a graduate-level degree in a technical discipline and at least 5 years of experience in production ML or AI systems. Proficiency in Python, PySpark, and production-grade GenAI implementation is required, along with experience in Azure and Databricks environments.

Skills

Machine learning
Generative AI
Python
PySpark
SQL
Prompt engineering
Azure
Databricks
MLOps
LLMOps
Data pipelines
Model validation
Feature engineering
Clustering
Classification
Software engineering

Benefits

Comprehensive benefits
Retirement programs
Performance incentives
Continuing education programs
Product discounts
Mental health benefits
Profit sharing

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Generative AI
Customer Intelligence
Python
PySpark
SQL
Azure
Databricks
MLflow
Azure Data Lake Storage
Azure Data Factory
Synapse
MLOps
LLMOps
Prompt Engineering
Foundation LLMs
Data Pipelines
Feature Engineering
Model Inference
Batch Inference
Retrieval-Augmented Generation
Semantic Search
Vector Databases
CI/CD
Containerization
Retail
Ecommerce
Recommendation Systems
Behavioral Modelling
Software Engineering

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