Job Description

"If you are excited about applying Machine Learning (ML) and Computer Vision (CV) to tackle real-world challenges in fine-grained recognition for the sports and gaming industry, this is a perfect opportunity for you. Be a part of the team of research and machine learning scientists building deployable real-world ML applications from ground up and get mentored by some of the best minds in AI during the process."


Xu Han, Machine Learning Scientist and Mara Cairo, Product Owner, Advanced Technology

About the Role

This is a paid Residency that will be undertaken over a twelve-month period with the potential to be hired by our client, TCG Machines, 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

TCG Machines is a Calgary-based robotics company that makes machines to sort trading cards.



Their core product is the PhyzBatch-9000 (pronounced "fizz-batch", a portmanteau of 'physical



Batch'), a robot capable of scanning, identifying, digitally cataloging, and physically separating



trading card game (TCG) cards, such as Pokemon and Magic: The Gathering. Every year, 25



billion new trading cards enter circulation globally, resulting in a massive inventory challenge for



the thousands of game stores that buy and sell those cards. These stores are the primary



customer base for TCG Machines. As of this writing, the collective fleet of PhyzBatch-9000



sorters have processed over 500 million cards - that's more than 1,000 tons of cards!!!

About the Project

The project aims to develop a robust multi-modal system that integrates computer vision and



natural language processing techniques to identify and classify sports/trading cards from image



and text data. A key challenge lies in resolving fine-grained distinctions between highly similar



cards, such as minor icon variations, foiled finishes, and unique serial numbers. This work will



involve curating and structuring large-scale datasets, designing novel model architectures that



combine visual features with OCR-extracted text, and exploring state-of-the-art deep learning



methods for image retrieval, recognition, and reasoning over imperfect or incomplete data. The



outcome of this research will be a scalable pipeline capable of accurate real-world card



identification and matching against a structured database.

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, computer vision, and image processing, along with proven experience in applied settings.

Key Responsibilities:

Design, implement, optimize, and evaluate computer vision models (including OCR models) and advanced image processing techniques to recognize sports and gaming cards. Prepare, curate, and preprocess high-quality datasets for training or fine-tuning, and validating models. Utilize state-of-the-art computer vision and ML frameworks, tools and open-source libraries to enhance model performance, accelerate workflows, and optimize data processing. Undertake applied research on ML and computer vision techniques to address the limitations in existing models. Optimize computer vision and image processing pipelines to ensure efficient, scalable, and real-time inference, while enabling robust performance on edge devices. 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 graduate level program or higher (M.Sc./Ph.D) in Computer Science, Machine Learning, or Engineering. Research and project experience in image processing, computer vision, and deep learning. Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, TensorFlow, PyTorch, OpenCV, Pandas, HuggingFace). 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:

Previous experience applying ML and computer vision in fine-grained image recognition tasks, such as facial recognition. Previous experience in applying OCR in image analysis tasks. Experience with building, training, evaluating, and quantizing machine learning models to achieve optimized performance in production environments, with a focus on low-latency, resource-efficient edge-device deployment. Knowledge of MKL, cuDNN, and acceleration techniques for math computing is a plus. Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus. Publication record in peer-reviewed academic conferences or relevant journals in ML or Applied AI (especially in computer vision).

Non-Technical Requirements:

Desire to take ownership of a problem and demonstrated 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 October 20, 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.