Machine Learning Engineer III, Tim Hortons

Ready to make your next big professional move? Join us on our journey to achieve our big dream of building the most loved restaurant brands in the world.

Restaurant Brands International Inc. is one of the world's largest quick service restaurant companies with nearly $45 billion in annual system-wide sales and over 32,000 restaurants in more than 120 countries and territories.

RBI owns four of the world's most prominent and iconic quick service restaurant brands – TIM HORTONS®, BURGER KING®, POPEYES®, and FIREHOUSE SUBS®. These independently operated brands have been serving their respective guests, franchisees and communities for decades. Through its Restaurant Brands for Good framework, RBI is improving sustainable outcomes related to its food, the planet, and people and communities.

RBI is committed to growing the TIM HORTONS®, BURGER KING®, POPEYES® and FIREHOUSE SUBS® brands by leveraging their respective core values, employee and franchisee relationships, and long track records of community support. Each brand benefits from the global scale and shared best practices that come from ownership by Restaurant Brands International Inc.

Tim Hortons® is one of North America's largest restaurant chains operating in the quick service segment, with more than 4,800 system wide restaurants located in Canada, the United States and around the world.

We are currently looking for experienced and driven Machine Learning Engineer to join our Advanced Analytics team. The Advanced Analytics team is responsible for the building, training, deploying, scoring, and monitoring of machine learning models for various use cases and across different functional areas, including but not limited to personalized recommender, forecasting, and LLM modelling. The Machine Learning Engineer will play a pivotal role in advancing our advanced analytics and machine learning capabilities within the organization.

RBI follows a 5 day, in-office work schedule to support collaboration. Candidates should be comfortable working onsite 5 days per week out of our office in Toronto, ON.

What You’ll Do:

Develop and deploy Machine Learning, Deep Learning and GenAI models to enhance operational efficiency and customer experience.

Continuously improve models by monitoring performance, conducting A/B testing, and implementing feedback loops.

Stay updated with the latest advancements in machine learning and AI to ensure our solutions remain cutting-edge.

Collaborate with cross-functional teams including engineers and product managers to integrate AI solutions into production systems.

Who You Are:

We are looking for individuals who:

Take ownership and manage strategic initiatives in a rapidly evolving QSR environment.

Eagerness to learn and adapt in ambiguous problem spaces with a collaborative attitude.

Collaborate with engineering and product teams to implement ML and GenAI solutions in production.

Focus on outcomes, analyze and visualize data to drive continuous improvement across the business.

Work effectively in a fast-paced Agile environment, maintaining transparency and professionalism in communication.

What You Bring:

Bachelor’s or advanced degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.

3+ years of experience designing, building, and operating production-scale machine learning systems as a Machine Learning Engineer, Senior Data Scientist, or similar role.

Expert-level programming in Python with extensive experience using PySpark and distributed data platforms (e.g., Databricks) to process and model large-scale datasets.

Proven ability to architect and rebuild complex ML frameworks from the ground up, incorporating multi-threaded processing, distributed workloads, and coordinated synchronous/asynchronous task management to support scalable data and model pipelines.

Deep understanding of distributed data processing frameworks, including Spark execution model, partitioning strategies, shuffle optimization, worker-level execution, and advanced techniques such as Pandas UDFs, vectorized processing, and large-scale performance tuning.

Strong experience developing and productionizing models using frameworks such as Scikit-Learn, MLlib, and PyTorch, with solid understanding of regression, time series, clustering, supervised/unsupervised learning, and deep learning.

Proven experience owning production ML systems, including participating in model on-call rotations, monitoring model performance and data distribution, troubleshooting incidents, and maintaining model reliability.

Strong SQL expertise for large-scale data manipulation and feature engineering.

Experience implementing MLOps / LLMOps practices and deploying ML workloads to cloud environments such as AWS (EC2, S3, DynamoDB, Lambda).

Base salary range of $100,000 – $130,000 CAD. Base salary for this position may vary based on relevant factors such as experience, education, location, and skills.

This position is eligible to participate in the Company’s annual discretionary bonus plan, subject to the terms and conditions of the incentive program, based on individual and company performance metrics. This position may also be eligible for additional compensation in the form of equity grants pursuant to the Company’s long-term incentive plan.

This posting is for an existing vacancy.

#TimHortons

Benefits at all of our global offices are focused on physical, mental and financial wellness. We offer unique and progressive benefits, including a comprehensive global paid parental leave program that supports employees as they their families, free telemedicine and mental wellness support.