Senior AI/Machine Learning Engineer
21 hours ago
, Canada
Canadian Tire Financial Services
Full-time
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## Senior ML/AI EngineerApply: Toronto, ON: Full time: Posted Today: End Date: September 22, 2026 (13 days left to apply): JR164829
What You'll Do
* Develop a deep understanding of our Retail business, Loyalty program, and how personalized offers are composed and delivered across our retail banners.
* Design and deliver offline evaluation frameworks with explicit success criteria — ranking metrics, held-out AUC, time-respecting splits, and point-in-time correctness — so that an offline win reliably predicts online lift.
* Research and apply modelling methodology to select (and justify) the right approach for a given business problem, from matrix factorization and two-tower retrieval to learning-to-rank and sequential architectures.
* Build and optimize large-scale feature engineering in PySpark over hundreds of millions of transaction records, with the profiling skills to know why a job is shuffling.
* Design and operate our ML platform layer — feature store, reproducible training pipelines, and cloud training job submission — so retraining is cheap and routine rather than a project.
* Design and implement agentic AI solutions that automate model improvement — extending our in-house harness where an AI agent proposes changes, scores them against a locked benchmark, and keeps only what measurably helps, under human review.
* Lead optimization and orchestration of end-to-end analytical pipelines across multiple data sources and modelling workstreams to ensure scalability and production reliability.
* Raise the engineering standard of the team through code review, documentation, and mentorship of engineers working adjacent to the model layer.What You Bring:* B.
S or M.
S, preferably in Computer Science/Statistics/Math/Engineering or a related quantitative discipline. PhD an asset.
* 3+ years experience developing and deploying machine learning solutions in production — owning data, training, evaluation, release, and operational support. Experience in retail, loyalty programs, personalization, or ad-tech ranking preferred.
* Expert-level Python, writing production-grade ML code rather than notebooks handed off for deployment.
* 4+ years of experience querying and analyzing large datasets with tools such as SQL and Spark, with demonstrated depth in PySpark.
* Demonstrated experience with recommender systems or large-scale ranking, and the judgment to know which technique a problem actually requires.
* Rigorous approach to offline evaluation — including train/validation splits that respect time, point-in-time correct feature construction, and leakage you have personally found and fixed.
* Experience with deep learning frameworks (PyTorch, TensorFlow) and gradient boosting libraries such as LightGBM or XGBoost.
* Production experience with a major cloud ML platform — Vertex AI preferred; SageMaker or Azure ML acceptable — including custom training jobs, artifact management, and cost control. Familiarity with BigQuery and cloud-based data structures is an asset.
* Experience designing and orchestrating multi-stage analytical pipelines with workflow optimization, preferably Apache Airflow at production scale.
* Familiarity with agentic AI architectures, LLM-based solutions, and working fluently with coding agents is a strong asset. Infrastructure-as-code experience (Terraform) and cloud IAM familiarity is an asset.
* Excellent oral and written communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills.
* Demonstrated ability to work independently with minimal supervision, effectively navigating and resolving ambiguous problems and situations.Location: Toronto, Ontario (Hybrid: In-office 4 days a 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 discountsBroadband Salary Range: $64,000
- $106,000. Our typical *hiring range
* is between $64,000 and $85,000. 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. #J-18808-Ljbffr
What You'll Do
* Develop a deep understanding of our Retail business, Loyalty program, and how personalized offers are composed and delivered across our retail banners.
* Design and deliver offline evaluation frameworks with explicit success criteria — ranking metrics, held-out AUC, time-respecting splits, and point-in-time correctness — so that an offline win reliably predicts online lift.
* Research and apply modelling methodology to select (and justify) the right approach for a given business problem, from matrix factorization and two-tower retrieval to learning-to-rank and sequential architectures.
* Build and optimize large-scale feature engineering in PySpark over hundreds of millions of transaction records, with the profiling skills to know why a job is shuffling.
* Design and operate our ML platform layer — feature store, reproducible training pipelines, and cloud training job submission — so retraining is cheap and routine rather than a project.
* Design and implement agentic AI solutions that automate model improvement — extending our in-house harness where an AI agent proposes changes, scores them against a locked benchmark, and keeps only what measurably helps, under human review.
* Lead optimization and orchestration of end-to-end analytical pipelines across multiple data sources and modelling workstreams to ensure scalability and production reliability.
* Raise the engineering standard of the team through code review, documentation, and mentorship of engineers working adjacent to the model layer.What You Bring:* B.
S or M.
S, preferably in Computer Science/Statistics/Math/Engineering or a related quantitative discipline. PhD an asset.
* 3+ years experience developing and deploying machine learning solutions in production — owning data, training, evaluation, release, and operational support. Experience in retail, loyalty programs, personalization, or ad-tech ranking preferred.
* Expert-level Python, writing production-grade ML code rather than notebooks handed off for deployment.
* 4+ years of experience querying and analyzing large datasets with tools such as SQL and Spark, with demonstrated depth in PySpark.
* Demonstrated experience with recommender systems or large-scale ranking, and the judgment to know which technique a problem actually requires.
* Rigorous approach to offline evaluation — including train/validation splits that respect time, point-in-time correct feature construction, and leakage you have personally found and fixed.
* Experience with deep learning frameworks (PyTorch, TensorFlow) and gradient boosting libraries such as LightGBM or XGBoost.
* Production experience with a major cloud ML platform — Vertex AI preferred; SageMaker or Azure ML acceptable — including custom training jobs, artifact management, and cost control. Familiarity with BigQuery and cloud-based data structures is an asset.
* Experience designing and orchestrating multi-stage analytical pipelines with workflow optimization, preferably Apache Airflow at production scale.
* Familiarity with agentic AI architectures, LLM-based solutions, and working fluently with coding agents is a strong asset. Infrastructure-as-code experience (Terraform) and cloud IAM familiarity is an asset.
* Excellent oral and written communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills.
* Demonstrated ability to work independently with minimal supervision, effectively navigating and resolving ambiguous problems and situations.Location: Toronto, Ontario (Hybrid: In-office 4 days a 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 discountsBroadband Salary Range: $64,000
- $106,000. Our typical *hiring range
* is between $64,000 and $85,000. 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. #J-18808-Ljbffr
