Sr. Machine Learning Engineer; Deep Learning Engineer
Job in
Regina, Saskatchewan, S4M, Canada
Listing for:
S.i. Systems
Contract
position
Listed on 2026-06-18
Job specializations:
-
IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, Data Engineering
Job Description & How to Apply Below
Position: Sr. Machine Learning Engineer (Deep Learning Engineer)
Our client is Canada’s largest retailer. They are looking for a Senior Machine Learning Engineer to develop and improve ML and deep learning models that power personalization across their retail ecosystem.
This role focused on model development using Python and PyTorch, with a strong emphasis on ownership, experimentation, and practical impact on experiences used by millions of Canadians daily.
Duration: 6 Months, to start
Location:
Remote
Responsibilities:
Develop, train, evaluate, and optimize deep learning models for personalization and recommendation systemsWork across the full model development lifecycle including data analysis, feature engineering, experimentation, training, validation, and evaluationDesign and implement PyTorch-based deep learning models for practical business use casesAnalyze model performance and iterate based on measurable metricsBuild reusable model training, inference, and evaluation workflowsCollaborate with product, data science, and engineering teams to deliver scalable personalization solutionsDocument experimentation results, model behavior, and technical trade-offs clearlyMust Have
Skills:
Hands-on experience developing Deep Learning Models in production environmentsStrong Python programming skills, strong hands-on experience with PyTorch (or similar deep learning frameworks)Strong understanding of deep learning fundamentals including training, validation, evaluation, optimization, overfitting, and generalizationExperience gathering, cleaning, analyzing, and preparing data for machine learning applicationsStrong software engineering practices including clean code, version control, testing, and documentationStrong sense of ownership with the ability to drive work forwardNice to Haves:
Experience with GCP, Big Query, SQL, Spark, Dataflow, Airflow, Kubernetes, or cloud-based ML workflowsExperience deploying and supporting ML models in production environmentsExperience with personalization, recommendation, search, ranking, or relevance systems
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