Senior Machine Learning Engineer

Loblaw Companies Limited • Toronto, ON

13d • Onsite

About The Position

At Loblaw Digital, we are committed to building the best, most innovative online shopping experiences across various verticals including online grocery, beauty, pharmacy, and apparel. From our office in Downtown Toronto, we are seeking a Senior Machine Learning Engineer to join our team. This role is crucial for the development, deployment, and testing of advanced AI systems and sophisticated search agents. The successful candidate will leverage Machine Learning and cutting-edge Large Language Models (LLMs) to build robust, scalable AI applications specifically for the Retail sector, and will also be responsible for mentoring other ML developers.

Requirements

• Bachelor’s degree or equivalent in Computer Science or a related field alongside a strong foundation in ML algorithms, ML pipelines, and transformations, with 5+ years of hands-on experience building scalable ML products.
• Software engineering proficiency in Python, SQL, and Design Patterns, with proven experience building and deploying ML solutions in microservices architecture in production.
• 2+ years experience using GCP tools in ML workflows like Vertex AI, BigQuery, Cloud Composer and Cloud Storage.
• Proven experience in LangChain ecosystem or other Agentic frameworks, NLP, LLMs, RAGs and embedding models.
• Skilled in ML workflow automation/deployment and MLOps for seamless integration and deployment, and have supported ML products in production environments.
• 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.

Responsibilities

• Design, build and ship multiple components within an Agentic AI system utilizing state of the art technologies to solve business problems.
• Develop high-performance enterprise-level Machine Learning models and AI agents using Python programming, leveraging massive structured and unstructured datasets and APIs from various internal and external sources.
• Champion and lead best practices for MLE and LLMOps.
• Collaborate with front end and back end engineering teams to build and deploy ML models and agentic components in production.
• Take ownership of system components, mentor other machine learning developers, and contribute to raising the technical bar within the team.
• Document and share results and findings with stakeholders in a structured manner and drive technical discussions cross functionally.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees