Machine Learning Scientist

at  Alberta Machine Intelligence Institute

“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

QUALIFICATIONS:

• Graduate degree (Masters or PhD) in Machine Learning or an engineering/scientific field with experience in Machine Learning
• 2+ years of experience developing, training, and evaluating machine learning models in an industrial setting
• Expert knowledge in machine learning theory & practice and its applications to challenges in an applied ML domain
• Publication record in peer-reviewed academic conferences or relevant journals
• Able to work with Jupyter notebooks and knowledge of version control systems. Comfortable with Python based ML and Deep Learning frameworks (e.g. Scikit-learn, Pytorch, Tensorflow, Keras, Transformers, JAX, and pandas).
• Ability to communicate technical topics to a non-technical audience
• General understanding of the strengths and weaknesses of a range of ML techniques across supervised learning, unsupervised learning, and reinforcement learning
• Up-to-date knowledge within their particular specialties

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 THE ROLE

The Machine Learning Scientist serves as a key member of the Advanced Technology Team and an active participant in maintaining Amii’s reputation for scientific excellence and providing insight into their area of expertise.
The Machine Learning Scientist (MLS) uses their scientific knowledge and applied research experience to direct the research and development efforts of Amii Industry Partners and Clients. They bridge the gap between business opportunities and fundamental ML techniques, providing scientific oversight on technical projects. They advise clients on the scoping and definition of machine learning projects and coach companies through the iterative stages of the Machine Learning Process Lifecycle (MLPL). This includes making informed decisions about what the data requirements are, what modelling techniques should be tested, what technical resources need to be onboarded when more background research is required, and how success will be evaluated.
The MLS is also responsible for providing leadership and mentorship to junior team members. The Advanced Tech team sources unique talent to work on our industry partner’s projects, and the MLS is responsible for supporting the talent throughout the project delivery.
Scientists empower Amii clients with the knowledge and skills they need to advance on the AI Adoption Spectrum by applying their unique combination of research and industry experience. They support Amii’s internal teams as subject matter experts based on their technical specialties and applied Machine Learning experience.

The role focuses on achieving excellence in three main accountabilities:

• Industry Engagement - Working with Amii clients to advance their ML projects and capabilities
• Stakeholder Satisfaction - Supporting Amii staff as subject matter experts
• Research - Supporting the advancement of ML research

KEY RESPONSIBILITIES:

• Define, design, and supervise the implementation of applied ML projects
• Supervise and mentor early career ML interns, residents, and associate MLSs on ML project work and career progression
• Advise industry and academic partners on machine learning projects
• Write technical reports and present on technical work
• Collaborate with clients, fellows, and team members on research papers
• Deliver on ML science requirements in a dedicated product stream