Machine Learning Scientist (12 month term)

“Are you passionate about innovating with AI at the intersection of industry and academia? Are you interested in contributing to ML projects that redefine what’s possible? If so, we want to hear from you! We’re seeking talented individuals to join our ML staff to work on projects spanning industries, specializations, and applications.”

- Dave Staszak, Lead Machine Learning Scientist 

About the Role

Reporting to the Lead Machine Learning Scientist, Advanced Technology, the Machine Learning Scientist, Advanced Technology serves as a key member in maintaining Amii's reputation for scientific excellence and providing insight into their area of expertise.

This position is responsible for the delivery of innovative solutions to Amii's industry partners by leading applied ML projects and mentoring junior team members. Their expertise bridges the gap between fundamental ML techniques and business opportunities, guiding clients through the complexities of AI adoption. 

The Advanced Technology team sources technical talent to work on our industry partners’ projects and the Machine Learning Scientist is responsible for supporting that talent through those project deliveries.

The position focuses on achieving excellence in four main accountabilities:

• Client Success: Work with Amii clients to advance their ML projects and capabilities.
• Machine Learning Expertise: Serve as a subject matter expert to guide and support organizational initiatives. 
• Research & Development: Support the advancement of ML research and development in both industry and academia.
• People Leadership: Mentor junior team members to help them achieve their goals and advance their professional growth. 

Required Skills / Expertise

Key Responsibilities:

Client Success 

• Leads regular client meetings to understand their machine learning objectives and provides tailored technical guidance to support project development
• Bridges the gap between fundamental ML techniques and business opportunities, providing scientific insight into technical projects
• Supports the implementation of exploratory data analysis and machine learning modelling techniques
• Conducts client discovery sessions to understand and determine specific needs and requirements
• Coaches clients to efficiently extract insights and make informed decisions
• Writes and reviews technical reports and code 
• Develops and nurtures strong relationships with clients through effective communication and scientific excellence 
• Incorporates client feedback to enhance delivery and ensure client success

Machine Learning Expertise

• Establishes themselves firmly as a trusted subject matter expert in a specific domain 
• Coaches junior staff through the model-building process, providing expertise and support 
• Mentors junior team members on career development and progression, drawing lessons for coaching opportunities
• Encourages a collaborative work environment by facilitating teamwork and the exchange of ideas among team members 
• Identifies and addresses knowledge gaps, providing solutions or resources to bridge them
• Ensures the Principled AI Framework is integrated into all projects, promoting ethical AI development and usage

Research and Development

• Translates academic research into practical applications, applied research and industry solutions
• Conducts research in leading-edge methods in various AI domains, such as reinforcement learning (RL), computer vision (CV), natural language processing (NLP) and large language models (LLMs)
• Transfers knowledge across domains and industries, building a strong technical repertoire to bring to new problems 
• Prepares manuscripts for publication in peer-reviewed journals
• Supports fundamental research in AI through applied research projects and the development of research topics

People Leadership

• Provides supervision to junior team members by overseeing and refining their work, and managing approval processes
• Mentors direct reports on career development and progression, drawing lessons for coaching opportunities
• Fosters a collaborative work environment by facilitating teamwork and the exchange of ideas among team members
• Encourages and maintains a problem-solving approach to work while acting as a coach and collaborator
• Identifies and addresses knowledge gaps, providing solutions or resources to bridge them
• Functions as a point of escalation for addressing challenges and facilitating the resolution of problems 

Qualifications: 

• Masters in Computer Science with a specialization in Machine Learning or related field with relevant applied experience in Machine Learning
• 2+ years experience developing, training, and evaluating machine learning models in an industrial setting
• 1+ years experience in a leadership capacity in industry or academic setting (nice to have)
• Proficient in Python, experience in other programming languages i.e. Java or SQL (nice to have)
• Proficient with machine learning tools and frameworks such as Scikit-learn, Pytorch, Pandas, Optuna, Wandb, lightgbm/XGBoost, and SciPy
• Publication record in peer-reviewed academic conferences or relevant journals 
• Ability to explain complex technical concepts clearly to non-technical audiences
• Thorough understanding of the strengths and weaknesses of a range of ML techniques across supervised learning, unsupervised learning, and reinforcement learning
• Experience leveraging cloud based tools for ML model building and deployment

Knowledge, Skills and Abilities (KSA): 

• Strong analytical and problem-solving abilities, with a keen attention to detail
• Flexibility and willingness to adapt, including working with disparate data, skill levels, and client needs
• Works independently and make informed decisions while collaborating with team members and subject matter experts 
• Able to identify gaps in knowledge and triage their own learning appropriately
• Comfortable taking a leadership role, providing expert scientific guidance and mentorship to both clients and junior team members
• Exhibits confidence and sound judgment while collaborating with subject matter experts

What you'll love about us

• A professional yet casual work environment that encourages the growth and development of your skills
• Participate in professional development activities
• Gain access to the Amii community and events
• A chance to learn from amazing teammates who support one another to succeed
• Competitive compensation, including paid time off and flexible health benefits
• A modern office located in downtown Edmonton, Alberta

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 July 30, 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.