Top Tech Jobs & Startup Jobs in Toronto

Lead end-to-end commercial sales into research organizations and R&D teams: prospect, qualify, demo, structure pilots, and close. Build relationships with physicists and research leaders, manage stakeholders, maintain CRM and forecasting, and feedback market insights to product and research teams to drive adoption and revenue.

Lead full-cycle technical recruiting for engineers and researchers: source hard-to-find talent, partner with hiring managers, conduct interviews, build talent communities, use recruiting data to improve processes, and shape employer brand and hiring strategy.

Work directly with physicists to drive adoption of an AI research platform: own user lifecycle from discovery to retention, design onboarding and scalable workflows, build guides and tooling, identify UX friction, and act as a technical point of contact while partnering with research and engineering.

Lead end-to-end operations for an AI-native Physicist Fellowship: recruit fellows, run selection processes, coordinate advisors and technical teams, design cohort programming, track metrics, and build ecosystem relationships to support AI-driven scientific research.

Identify, close, and operationalize strategic partnerships with AI labs, infrastructure providers, and research organizations. Lead end-to-end partnership discussions, define technical integration details (APIs, data schemas, compute/tooling exchanges), collaborate with engineering and research teams, negotiate granular commercial and technical terms, and ensure agreements become functioning integrations that deepen long-term collaboration.

Lead a team of 4–6 engineers to turn research prototypes into reliable, scalable systems. Establish technical strategy, architecture, and squad-level outcomes; bridge research and engineering; build testing, observability, deployment, and operational practices; mentor engineers and influence hiring and organizational design across the company.

Lead a team of researchers to define and execute high-impact research programs bridging ML, scientific domains, and product. Shape hypotheses, experiments, models, data strategy, evaluations, and implementations while mentoring researchers and driving research into validated, reusable capabilities and deployed systems.

First in-house legal counsel to build and lead a global legal function for an AI research organization. Responsible for AI governance, IP strategy, data licensing, cross-border corporate governance, nonprofit compliance, vendor and collaboration agreements, talent program legal frameworks, and advising leadership on risk and regulatory issues across Canada, the US, and other jurisdictions.