Senior Machine Learning Engineer, Retail Media Platform

At Loblaw Digital, we know that our customers expect the best from us. Whether that means building the best, most innovative online shopping experiences, or designing an app that will impact the lives of people across the country, we’re up for the challenge. Loblaw Digital is the team responsible for building and operating the online businesses of Canada’s largest and most successful retailer. Based in downtown Toronto, we are an entrepreneurial, fast-paced, and collaborative team working towards transforming the way Canadians shop by creating leading eCommerce experiences in the online grocery shopping, beauty, pharmacy, loyalty, and apparel spaces, and we’re only just getting started! To achieve these goals, we are looking for talented and passionate individuals who want to collaborate and solve challenging problems and make significant and lasting impact on Canadians.

As a Senior Machine Learning Engineer on our team, you will use an abundance of data from the Loblaw enterprise in order to build machine learning solutions. Your team will collaborate with business stakeholders and engineers within Loblaw Digital to deliver models to production that help in driving our Ecommerce business including Search, Recommendations, Media and Supply Chain optimization. You will design experiments to measure your success with KPIs that include adoption, conversion & retention. You will use data every single day to uncover meaningful insights that inform your experimentation strategy and ultimately, your product roadmap.

What you’ll do

• Design, build, and maintain highly scalable, robust, and efficient cloud infrastructure using Google Cloud Platform (GCP) services, including Vertex AI, BigTable, BigQuery, and Cloud Composer.
• Develop automation and orchestration of ML pipelines, integrating data ingestion, feature engineering, training, and deployment processes.
• Collaborate with cross-functional teams to understand their needs and build solutions that improve platform usability, scalability, and the overall development experience.
• Optimize data processing pipelines and cloud resources to ensure low-latency, cost-effective operation.
• Implement monitoring, alerting, and failover strategies to ensure platform reliability.
• Stay updated with industry trends and best practices in cloud engineering, data engineering, and machine learning

Does this sound like you?

• Customer-centric mindset: Passionate about delivering an exceptional experience for data scientists through a self-service platform, reducing friction in their workflows.
• Collaboration: Strong communication skills to work closely with cross-functional teams, including data scientists and engineers, to ensure platform features meet user needs and expectations.
• Problem-solving: Ability to identify and solve complex technical issues related to ML pipelines, cloud infrastructure, and scalability, ensuring an efficient and robust platform.
• Automation-first approach: Commitment to streamlining and automating processes for scalability and reliability, enabling data scientists to focus on experimentation and model development.
• Adaptability: Ability to quickly adjust to new technologies and evolving platform needs to keep the infrastructure cutting-edge and efficient.
• Ownership and initiative: Comfortable taking ownership of key platform components, driving innovation and improvements that benefit the platform’s scalability and usability.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 2+ years of experience in software engineering with a focus on cloud infrastructure and/or data engineering.
• Hands-on experience with Google Cloud Platform services such as Vertex AI, BigTable, BigQuery, Cloud Composer, Cloud Storage, etc.
• Proficiency in one or more programming languages such as Python, Java, and SQL.
• Experience with orchestration tools such as Apache Airflow (Composer).
• Knowledge of CI/CD pipelines and DevOps tools for continuous integration and deployment.
• Familiarity with containerization and orchestration (Docker, Kubernetes).
• Strong problem-solving skills and attention to detail.
• Excellent communication skills and ability to work in a collaborative, fast-paced environment