Computer Vision Jobs in Toronto, ON (NOW HIRING)

Location: REMOTE / Toronto, Ontario. This job allows you to work remotely.

Toronto is the primary preferred location. Montreal is the second. Third could be across Canada.

We are a pioneering, venture-backed, early-stage technology company developing a core, computer vision-heavy automation platform for the industrial design and spatial planning sectors. Our technology leverages deeply integrated AI to transform complex physical schematics into accurate datasets. Having operated successfully for several years with a lean, highly technical core team, we are scaling our operations and entering a critical phase of organizational growth.

As the Head of Engineering, you will assume full ownership of the technology organization, transitioning delivery responsibilities away from product founders. This is a high-impact, player‑coach leadership position—not an insulated corporate executive role. You will bridge the gap between high‑level business strategy and deep technical execution, earning immediate respect from a sophisticated engineering team while driving predictable delivery timelines, architectural scaling, and operational maturity.

• Cross-Functional Alignment: Align engineering roadmaps with Product and Go-to-Market functions through structured operating cadences and clear planning cycles.
• Executive Communication: Act as the primary technical voice to executive leadership, translating technical complexities, dependencies, and risk factors into strategic business outcomes.
• Execution Accountability: Establish objective quarterly performance targets and execution frameworks for engineering leads to maintain predictability and velocity.

• Technical Vision: Define the long-term technical roadmap, leading core architectural decisions for scalable, multi-tenant cloud infrastructure and data-driven systems.
• Hands‑on Guidance: Allocate roughly 10%–20% of your time to technical engagement, including architectural design reviews, proof-of-concept development, and code quality oversight.
• Engineering Excellence: Balance rapid business delivery with technical sustainability by setting rigorous standards for system performance, application security, and technical debt management.

• Platform Infrastructure: Supervise the evolution of developer platforms, automated CI/CD pipelines, and robust testing frameworks.
• Reliability & Observability: Modernize system reliability and operational monitoring, overseeing vendor‑managed external QA teams and driving structured incident response protocols.
• Operational Metrics: Utilize precise data metrics (e.g., deployment frequency, lead time, MTTR) to systematically isolate bottlenecks and optimize development throughput.

• Structure & Design: Assess current capabilities to design an expanded engineering structure, preparing to scale the internal technical team by roughly 50% over the next two quarters.
• Talent Pipelines: Implement repeatable strategies for technical sourcing, structured onboarding, engineering mentorship, and sustainable retention.
• Team Culture: Cultivate a transparent, high‑ownership technical culture that balances deep engineering focus with commercial awareness and strong communication.

• Scale‑Up Experience: Proven history of leading engineering teams through the distinct 0-to-1 and early scale-up phases within high-growth SaaS environments.
• Technical Leadership Scope: Prior experience operating successfully as a Startup CTO, Head of Engineering, Technical Co‑Founder, or Director of Engineering over high-performing multi-pod technical organizations.
• Deep Architecture Expertise: Extensive experience defining scalable architectures for high‑scale, distributed cloud systems and multi-tenant applications.
• Full-Stack Ecosystem Familiarity: Strong technical fluency within modern backend environments (specifically Python ecosystems, including web frameworks and database management) alongside modern JavaScript/TypeScript frontends.
• AI Tooling Adoption: Active, practical adoption of modern AI productivity platforms, developer assistants, and autonomous agent workflows within daily engineering cycles.
• Communication & Business Acumen: Exceptional verbal and written English communication skills, with the capability to interface cleanly with commercial stakeholders and executive leadership.
• Education: A University Degree in Computer Science, Software Engineering, or a strictly related quantitative technical field.

• Domain Exposure: Prior experience within automated estimation spaces, industrial blueprints, complex spatial modeling, or CAD‑adjacent software environments (e.g., Autodesk, Miro, Figma ecosystems).
• Advanced Technology Stack: Background working in product environments centered around computer vision, data pipelines, or automated document processing.