Come make your difference in communities across Canada, where authenticity, trust and making connections is valued – as we shape the future of Canadian retail, together. Our unique position as one of the country’s largest employers, coupled with our commitment to positively impact the lives of all Canadians, provides our colleagues a range of opportunities and experiences to help Canadians Live Life Well®.
At Loblaw Companies Limited, we succeed through collaboration and commitment and set a high bar for ourselves and those around us. Whether you are just starting your career, re-entering the workforce, or looking for a new job, this is where you belong.

Key Responsibilities

• Develop and implement robust Machine Learning (ML) solutions and scalable data pipelines, contributing to the full ML lifecycle from data preparation to deployment and monitoring.
• Collaborate on the architecture and implementation of MLOps pipelines to automate and streamline model deployment, versioning, monitoring, and governance.
• Contribute to the implementation and optimization of scalable, secure, and reliable ML infrastructure, leveraging Google Cloud Platform (GCP).
• Work closely with cross-functional teams including product, engineering, analytics, and business stakeholders to deliver high-quality data and ML solutions supporting analytics, reporting, and GenAI initiatives.
• Ensure data integrity, governance, security, and compliance in all data engineering and ML efforts.
• Monitor the performance and quality assurance of ML systems, identifying opportunities for continuous optimization.
• Stay current with emerging technologies and industry trends in data engineering, ML, and GenAI, applying new knowledge to enhance our solutions.
• Participate in project delivery and technical planning to ensure successful execution of data and ML projects.

Required Qualifications

• Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a related field.
• 1-2 years of hands-on experience in Data Science, ML engineering, or a related technical domain.
• Proven experience in designing and implementing data platforms and ML systems on cloud platforms, preferably GCP.
• Strong technical knowledge of data/ML architecture, ML models, ETL/ELT processes, and distributed computing frameworks.
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and experience with MLOps tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines).
• Experience designing CI/CD pipelines
• Excellent communication, problem-solving, and collaboration skills, with the ability to work effectively within a team.

Our commitment to Sustainability and Social Impact is an essential part of the way we do business, and we focus our attention on areas where we can have the greatest impact. Our approach to sustainability and social impact is based on three pillars – Environment, Sourcing and Community – and we are constantly looking for ways to demonstrate leadership in these important areas. Our CORE Values – Care, Ownership, Respect and Excellence – guide all our decision-making and come to life through our Blue Culture. We offer our colleagues progressive careers, comprehensive training, flexibility, and other competitive benefits – these are some of the many reasons why we are one of Canada’s Top Employers, Canada’s Best Diversity Employers, Canada’s Greenest Employers & Canada’s Top Employers for Young People.
If you are unsure whether your experience matches every requirement above, we encourage you to apply anyway. We are looking for varied perspectives which include diverse experiences that we can add to our team.
We have a long-standing focus on diversity, equity and inclusion because we know it will make our company a better place to work and shop. We are committed to creating accessible environments for our colleagues, candidates and customers. Requests for accommodation due to a disability (which may be visible or invisible, temporary or permanent) can be made at any stage of application and employment. We encourage candidates to make their accommodation needs known so that we can provide equitable opportunities.

• Develop and implement robust Machine Learning (ML) solutions and scalable data pipelines, contributing to the full ML lifecycle from data preparation to deployment and monitoring.
• Collaborate on the architecture and implementation of MLOps pipelines to automate and streamline model deployment, versioning, monitoring, and governance.
• Contribute to the implementation and optimization of scalable, secure, and reliable ML infrastructure, leveraging Google Cloud Platform (GCP).
• Work closely with cross-functional teams including product, engineering, analytics, and business stakeholders to deliver high-quality data and ML solutions supporting analytics, reporting, and GenAI initiatives.
• Ensure data integrity, governance, security, and compliance in all data engineering and ML efforts.
• Monitor the performance and quality assurance of ML systems, identifying opportunities for continuous optimization.
• Stay current with emerging technologies and industry trends in data engineering, ML, and GenAI, applying new knowledge to enhance our solutions.
• Participate in project delivery and technical planning to ensure successful execution of data and ML projects