
Alberta Machine Intelligence Institute grows Alberta’s AI and machine learning capacity and helps organizations adopt machine intelligence. It advances research in AI and machine learning and translates that research into industry adoption through education, training, and business advisory services. Amii operates as a non-profit national AI institute affiliated with the University of Alberta and runs research labs, applied projects, and workforce development programs. The institute works with industry partners across sectors to build in-house AI capabilities and scale academic advances into commercial and operational use.

Alberta Machine Intelligence Institute grows Alberta’s AI and machine learning capacity and helps organizations adopt machine intelligence. It advances research in AI and machine learning and translates that research into industry adoption through education, training, and business advisory services. Amii operates as a non-profit national AI institute affiliated with the University of Alberta and runs research labs, applied projects, and workforce development programs. The institute works with industry partners across sectors to build in-house AI capabilities and scale academic advances into commercial and operational use.
“If you are interested in the application of machine learning and signal processing for real-time fraud detection, this is the right opportunity for you. You will be part of a team of research and machine learning scientists building production-ready fraud detection systems from the ground up and will receive mentorship from experienced researchers and practitioners in the field.” - Mara Cairo, Product Owner, Advanced Technology
Description About the Role
This is a paid residency that will be undertaken over a 12-month period with the intention to be hired by our client, Blue Raven, 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 Blue Raven is a well-funded Canadian startup operating in stealth mode and focused on applying advanced AI techniques to the detection and prevention of financial fraud. The company is building an AI-native platform designed to operate in real-time, with a strong emphasis on accuracy, reliability, and continuous learning. Blue Raven has validated market demand and developed a working proof of concept, and is now transitioning from early technical validation to scaled product development. The team is intentionally small, highly technical, and focused on building durable IP at the intersection of applied machine learning and real-world fraud prevention.
Blue Raven’s founding team has a track record of building successful startups from the ground up. Brian Heath, a 3-time founder with
multiple successful exits and 13 patents, brings deep expertise in building products that scale. Rob Fraser, our technical leader, brings 26 years of hands-on development experience and over a decade of engineering leadership.
About The Project This project focuses on advancing an AI-driven financial fraud detection system by transforming an existing decision-management framework into a continuously learning model. The work emphasizes improving classification accuracy, reducing false positives and false negatives, and designing learning algorithms that adapt over time with human oversight. The project will involve assessing and prioritizing AI modeling opportunities, improving data labeling and evaluation practices, and documenting scalable approaches to learning-based fraud detection across audio and text modalities. The outcome is a robust, production-oriented learning system that balances accuracy, performance, and reliability while remaining adaptable to evolving fraud patterns.
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, particularly in building systems that combine audio signals and text transcripts to detect fraud in real time. You will help extend an existing fraud detection system by implementing agentic workflows, improving false-positive evaluation and mitigation, and enabling the system to learn over time with human oversight.
Key Responsibilities
Required Qualifications
Preferred Qualifications
Non-Technical Requirements
Why You Should Apply
Besides Gaining Industry Experience, Additional Perks Include
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 27, 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.