“If you are interested in the application of machine learning for large-scale personalized customer engagement, this is the right opportunity for you. Be a part of the team of research and machine learning scientists building a next-generation personalization engine from the ground up and get mentored by some of the best minds in AI during the process.”

• Soumik Farhan, Machine Learning Scientist

Description About the Role

This is a paid residency that will be undertaken over a 12-month period with the potential to be hired by our client, Craver, afterwards (note: at the discretion of the client). The Resident will report to an Amii Scientist and regularly consult with the client team to share insights and engage in knowledge transfer activities. Successful candidates will be members of a cross-functional project team with backgrounds in ML research, project management, software engineering, and new product development. This is a rare opportunity to be mentored by world-class scientists and to develop something truly impactful.

About The Client Craver is a leading provider of custom-branded mobile apps for the restaurant industry, specializing in features like loyalty & rewards, subscription services, and single tap reordering. We are dedicated to transforming customer engagement for quick-service restaurants and coffee shops, working with local brands such as Stumptown Coffee, Rook and Go Get Em Tiger, as well as many other restaurants across North America.

About The Project With this project, you will drive the evolution of Craver's platform, building a dynamic, predictive personalization engine. The ultimate vision is to provide the right offer to the right guests via the right medium at the right time. Your work will enable a new level of platform intelligence, transforming behavioral data into automated, high-value guest experiences.

You will focus on developing and deploying Supervised Machine Learning models to solve for “The Right Offer” and “The Right Medium”. You will be responsible for implementing these models in a low-latency environment to deliver high-impact recommendations at scale. Your work will establish the decision-making framework required to optimize customer order size and frequency across various touchpoints, ensuring that the platform intelligently balances offer relevance with the most effective delivery method.

Required Skills / Expertise Are you passionate about building great solutions? You’ll be presented with opportunities to both personally and professionally develop as you build your career. We’re looking for a talented and enthusiastic individual with a solid background in machine learning, specifically Recommender Systems and Personalization.

Key Responsibilities

• Design, implement, optimize, and evaluate models for user targeting, content personalization, and recommendation tasks.
• Prepare, curate, and preprocess high-quality datasets for training or fine-tuning, and validating models.
• Design multi-objective ranking systems to balance conflicting goals, such as maximizing user relevance while minimizing notification fatigue and churn risk.
• Utilize state-of-the-art Recommender Systems and ML frameworks, tools and open-source libraries to enhance model performance, accelerate workflows, and optimize data processing.
• Undertake applied research on ML and personalization techniques to address the limitations in existing models.
• Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities.
• Collaborate with the project team and stakeholders to develop MVP and client focused solutions.
• Engage in regular client meetings, contributing to presentations and reports on project progress.

Required Qualifications

• Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in Recommendation Systems or Consumer Behavior Analysis based projects.
• Proficient in developing and training, fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.
• Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, PyTorch, Pandas, HuggingFace).
• Solid understanding of classical statistics and its application in model validation.
• Familiarity with Linux, Git version control, and writing clean code.
• A positive attitude towards learning and understanding a new applied domain.
• Must be legally eligible to work in Canada.

Preferred Qualifications

• Familiarity with and hands-on experience with large-scale transactional logs and user behavioral data.
• Publication record in peer-reviewed academic conferences or relevant journals in machine learning.
• Experience/familiarity with software engineering best practices.
• Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.

Non-Technical Requirements

• Desire to take ownership of a problem and demonstrate leadership skills.
• Interdisciplinary team player enthusiastic about working together to achieve excellence.
• Capable of critical and independent thought.
• Able to communicate technical concepts clearly and advise on the application of machine intelligence.
• Intellectual curiosity and the desire to learn new things, techniques, and technologies.

Why You Should Apply

Besides Gaining Industry Experience, Additional Perks Include

• Work under the mentorship of an Amii Scientist for the duration of the project
• Participate in professional development activities
• Gain access to the Amii community and events
• Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)
• Build your professional network
• The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)

About Amii One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

How to Apply

If this sounds like the opportunity you've been waiting for, please don’t wait for the closing January 5, 2026 to apply - we’re excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won’t be used in the selection process.