Machine Learning Engineer, Agentic AI

Loblaw Companies Limited; Toronto; On-site; CAD 120,000 - 154,000; Full time

Job summary

A leading eCommerce provider in Toronto is looking for an experienced Machine Learning Engineer to develop and deploy advanced AI systems. You will leverage ML to build scalable applications, collaborate with team members, and stay updated on industry trends. The ideal candidate should have a Bachelor's degree, strong skills in Python and SQL, and experience with GCP tools. This full-time position offers a salary range of $120,000 - $154,000 per year.

Qualifications

• 2+ years of hands-on experience building scalable ML products.
• Proficient in deploying ML solutions in microservices architecture.
• Strong foundation in ML algorithms, pipelines, and transformations.

Responsibilities

• Build and deploy components within an AI system using state-of-the-art technologies.
• Develop enterprise-level Machine Learning models using Python.
• Collaborate with team members to test and deploy system components.

Skills

Machine Learning products development

Python

SQL

Collaboration

Problem-solving

Education

Bachelor’s degree in Computer Science or related field

Tools

GCP tools (Vertex AI, BigQuery)

Docker

Kubernetes

Apache Airflow

Job description

At Loblaw Digital, we know that our customers expect the best from us. Whether that means building the best, most innovative online shopping experience, or designing an app that will impact the lives of people across the country, we’re up for the challenge. From our office in Downtown Toronto, we’ve created leading eCommerce experiences in the online grocery shopping, beauty, pharmacy, and apparel spaces, and we’re only just getting started.

Why is this role important?

We are seeking an experienced Machine Learning Engineer to join our team, focusing on the development and deployment of advanced AI systems and sophisticated search agents. This role involves leveraging ML and cutting-edge Large Language Models (LLMs) for building robust, scalable AI applications in the Retail vertical.

What you’ll do:

• Build and deploy components within an Agentic AI system utilizing state of the art technologies to solve business problems.
• Develop high-performance, scalable, enterprise-level Machine Learning models, pipelines and AI agents using Python code.
• Participate in team discussion, scrum ceremonies and design meetings on the different AI products you work on.
• Collaborate with team mates to review, test and deploy system components and code.
• Stay updated with industry trends and best practices in machine learning and conduct experiments and PoCs as needed within different AI projects.
• Document and share your work cross functionally in a structured standardized manner (e.g. UML diagrams, design documentation).

Who you are:

• Customer-First Mindset – Passion for building AI products that make people's lives easier and allow them to focus on what is important to them.
• Strong Collaboration – Excellent communication skills and ability to thrive in a collaborative, fast-paced environment.
• Problem-Solving Excellence – Analytical thinker who can identify, diagnose, and resolve technical challenges in ML pipelines and scalability.
• Automation-First Approach – You are always thinking about automation and are comfortable using AI for productivity.
• Adaptability & Innovation – Willingness to quickly learn new technologies and continuously improve the system.
• Ownership & Initiative – Ability to take ownership of your work and drive it to production.

Qualifications:

• Bachelor’s degree or equivalent in Computer Science or a related field alongside a strong foundation in ML algorithms, ML pipelines, and transformations, with 2+ years of hands-on experience building scalable ML products.
• Software engineering proficiency in Python, SQL, and Design Patterns, with proven experience deploying ML solutions in microservices architecture.
• Experience using GCP tools like Vertex AI, BigQuery, Cloud Composer and Cloud Storage.
• Knowledge in LangChain ecosystem or other Agentic frameworks, NLP, LLMs, RAGs and embedding models.
• Skilled in distributed data processing, ML workflow automation (Apache Airflow), CI/CD practices, and MLOps for seamless integration and deployment.
• Committed to code quality at every stage of the ML lifecycle, with a strong mindset in testing methodologies (unit, integration, end-to-end) and container orchestration using Docker and Kubernetes.

How You’ll Succeed:

At Loblaw Digital, we seek great people to continually strengthen our culture. We believe great people model our values, are authentic, build trust and make connections. We’re able to keep innovating because our colleagues are passionate about their work and excited about the future of eCommerce. If you have big ideas, undeniable enthusiasm, and thrive in a collaborative, creative, and diverse group, we’ll get along just fine. Looking for a challenge? Good. Love an innovative work environment? Even better. Apply today.

Employment Type: Full time

Type of Role: Regular

Loblaw Digital recognizes Canada's diversity as a source of national pride and strength. We have made it a priority to reflect our nation’s evolving diversity in the products we sell, the people we hire, and the culture we create in our organization. Accommodation is available upon request for applicants with disabilities in the recruitment and assessment process and when hired.

In addition, we believe that compliance with laws is about doing the right thing. Upholding the law is part of our Code of Conduct – it reinforces what our customers and stakeholders expect of us.

Hiring Range / Échelle salariale à l’embauche : $120,000.00 - $154,000.00 (per year / par an). A candidate’s experience and knowledge as well as the geographical region in which the position is located may be factored into the pay a candidate receives for this position. This posting is for an existing vacancy. The Company uses artificial intelligence for the purpose of screening, assessing and/or selecting applicants for this position.