LOCATION: This position can be based anywhere in Canada, with a preference for candidates situated in the eastern or central time zones to facilitate collaboration with our teams in the US, Europe, and India.ABOUT THE ROLEWiser Solutions is on the lookout for a Principal Machine Learning Engineer to lead and implement our AI and data science strategy. This senior technical leadership position requires an individual with profound expertise in machine learning, data science, and production engineering, complemented by the business insight needed to translate complex capabilities into customer value.As the technical authority for AI at Wiser, you will set architectural direction, communicate our capabilities to customers and partners, and deliver production systems that yield measurable business outcomes. This role demands proficiency in both strategic planning and hands-on implementation, allowing you to present to executives while also debugging production pipelines in the same week.We are cultivating an AI-native engineering culture at Wiser, where AI tools and techniques are integral to our workflows, not just the products we develop. We need a Principal AI Engineer who not only delivers AI products but also exemplifies AI-enhanced work methodologies and aids the broader engineering team in their adoption. If you are passionate about the transformative potential of AI in software development and implement that transformation in your daily activities, we want to hear from you.What You Will DoStrategic LeadershipDefine and enhance Wiser's AI and data science technical strategy in collaboration with product and business leadership.Articulate Wiser's AI capabilities to customers, partners, and advisors—clarifying our approach, roadmap, and unique offerings.Identify high-impact opportunities where AI can solve customer challenges or provide a competitive edge.Develop technical standards, patterns, and best practices that shape engineering decisions across the organization.Technical ExecutionArchitect and build production AI systems, including LLM applications, RAG pipelines, semantic search, and traditional ML models.Create rigorous evaluation frameworks, experimentation methodologies, and monitoring systems that ensure AI solutions yield reliable, measurable results.Integrate classical data science methods (statistical modeling, experimentation design, feature engineering) with modern generative AI approaches.Oversee technical quality for AI systems across the board: from data pipelines to model deployment and production observability.Cross-Functional ImpactCollaborate with product management to convert business requirements into technical solutions and validate these solutions against customer needs.Mentor and elevate the AI/data science team (3-5 engineers), enhancing the technical capabilities of the team.
Feb 26, 2026