Wave is hiring a Machine Learning Engineer in Toronto!
Wave, a company focused on helping small businesses succeed, is hiring a Machine Learning Engineer in Toronto. The role is positioned as an experienced individual contributor who will help design, develop, and deploy foundational AI and machine learning models. The engineer will also build robust, scalable ML pipelines and platforms that enable advanced analytics and business intelligence across the organization. The listing emphasizes reliability, efficiency, and tight integration of ML systems with broader business goals. Wave describes a creative, energetic environment where boldness, fast learning, and generous knowledge-sharing are valued. Because the posting is brief, it does not outline a detailed technical stack, formal education requirements, or a specific hybrid/remote policy. The opportunity is best suited to someone who can contribute across the ML lifecycle, from model development through deployment and platform support, while collaborating with others to make machine learning systems dependable and useful. Compensation is not stated in the listing.
Key responsibilities
- Design, develop, and deploy foundational AI and machine learning models.
- Build robust, scalable machine learning pipelines and platforms.
- Support advanced analytics and business intelligence through ML systems.
- Ensure ML systems are efficient, reliable, and aligned with organizational goals.
- Contribute as a key member of an experienced engineering team and share knowledge generously.
Key requirements
- Experience designing, developing, and deploying machine learning models.
- Ability to build and maintain scalable ML pipelines and platforms.
- Comfort working across model development, deployment, and production reliability.
- Ability to integrate ML systems with broader business and analytics objectives.
- Strong collaboration skills and willingness to learn quickly and share knowledge.
- Seniority: Experienced individual contributor
- Work mode: Not specified
- Key skills: Machine learning, AI models, ML pipelines, Scalable platforms, Model deployment, Advanced analytics, Business intelligence
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