About the job
LOCATION: This position can be based anywhere in Canada, with a preference for candidates in the eastern or central time zones to collaborate effectively with our teams in the US, Europe, and India.
ABOUT THE ROLE
Wiser Solutions is on the lookout for a Principal Machine Learning Engineer to steer and implement our AI and data science initiatives. This senior technical leadership role requires a unique individual who possesses extensive knowledge in machine learning, data science, and production engineering, coupled with the business insight needed to transform intricate capabilities into tangible customer value.
In this role, you will serve as the leading technical authority on AI at Wiser. Your responsibilities will include defining the architectural vision, showcasing our capabilities to clients and partners, and delivering production systems that yield measurable business results. This position demands an individual who can seamlessly navigate between strategic planning and hands-on execution, capable of engaging with executives one day and troubleshooting production pipelines the next.
We are fostering an AI-driven engineering culture at Wiser, where AI tools and methodologies are integrated into our workflows—not just our products. We seek a Principal AI Engineer who not only develops AI solutions but also exemplifies AI-enhanced working practices and aids the broader engineering team in their adoption. If you’re passionate about the transformative power of AI in software development and actively embrace this shift in your daily work, we want to hear from you.
Key Responsibilities
Strategic Leadership
- Collaborate with product and business leadership to define and refine Wiser's technical AI and data science strategy.
- Communicate Wiser's AI capabilities to clients, partners, and advisors, outlining our approach, roadmap, and unique value proposition.
- Spot high-impact opportunities where AI can effectively address client challenges or provide competitive advantages.
- Set technical standards, patterns, and best practices that guide engineering decisions across the organization.
Technical Execution
- Design and develop production AI systems, including applications for LLM, RAG pipelines, semantic search, and traditional ML models.
- Create rigorous evaluation frameworks, experimentation methodologies, and monitoring systems that ensure AI solutions deliver reliable, measurable outcomes.
- Integrate classical data science techniques (statistical modeling, experimentation design, feature engineering) with modern generative AI methods.
- Oversee the technical quality of AI systems end-to-end, from data pipelines and model deployment to production observability.
Cross-Functional Collaboration
- Work alongside product management to translate business needs into technical solutions and validate them against customer expectations.
- Guide and uplift the AI/data science team (3-5 engineers), enhancing the technical proficiency across the board.

