Machine Learning Resident

"If you are interested in the application of forecasting models for workforce management and optimization, this is the right opportunity for you. Be a part of the team of research and machine learning scientists building state-of-the-art models from the ground up and get mentored by some of the best minds in AI during the process."

• Shadan Golestan, Machine Learning Scientist and Mara Cairo, Product Owner, Advanced Technology

About the Role

This is a paid residency that will be undertaken over a 12-month period. 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 develop something truly impactful.

About the Client

Coconut Software bridges the gap between complex branch operations and high-value customer engagements with a suite of Intelligent Branch Solutions. The result: streamlined operations, enhanced customer experiences, and empowered staff focused on meaningful work. Its unified platform combines appointment scheduling, in-branch queuing, and video banking to help financial institutions tackle critical challenges head-on—maximizing resources, improving efficiency, and directly impacting customer satisfaction scores.

Trusted by leading banks and credit unions across North America—including RBC, Mountain America Credit Union (MACU), and M&T Bank—Coconut Software helps financial institutions optimize workforce planning, streamline branch traffic, and achieve revenue goals.

About the Project

This is a high-impact R&D project that sits at the exciting intersection of advanced analytics, operations research, and financial technology. The core challenge is to forecast customer demand within physical bank branches across multiple dimensions—not just how many customers will arrive, but for what services, with what skills (e.g., language), and when.

As the Machine Learning Resident, you will be instrumental in developing the models that provide these forecasts. You will then help design and build the recommendation engines that use these predictions to provide data-driven workforce recommendations. This is an opportunity to develop state-of-the-art models that will directly help financial institutions become more efficient and dramatically improve their customer experience.

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 and statistics, specifically generative models, like transformers, and sequential decision making algorithms, like Bayesian Optimization, or Reinforcement Learning.

Key Responsibilities:

• Design, implement, evaluate, and optimize forecasting models, for AI-driven simulation methodologies and optimization algorithms for demand forecasting and workforce optimization tasks
• Prepare, curate, and preprocess high-quality datasets for training and validating models.
• Undertake applied research to address the limitations in existing methods.
• 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.
• Compile and document project methodologies, experimental setups, analyses, and key findings.

Required Qualifications:

• Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in Sequential Decision Making algorithms (Bayesian Optimization and/or Reinforcement Learning) and experimental architecture simulation methodologies.
• Knowledge of modern forecasting models, particularly transformer-based approaches.
• Knowledge of classical time-series analysis and forecasting (e.g., moving averages, trend decomposition, seasonality).
• Proficient in developing and training machine learning models and sequential decision making algorithms in PyTorch.
• Strong publication record in top-tier AI/ML conferences and journals
• Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, BoTorch, OpenBox, Gymnasium, PyTorch, Pandas, HuggingFace).
• Solid understanding of classical statistics and its application in model validation.
• Familiarity with Linux, Git version control, and writing clean code.
• Experience/familiarity with software engineering best practices.
• A positive attitude towards learning and understanding a new applied domain .
• Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.

Non-Technical Requirements:

• Must be legally eligible to work in Canada.
• 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

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 November 19, 2025 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