Top Tech Jobs & Startup Jobs in Toronto

The Principal Engineer will design scalable backend services and APIs, optimize performance, and improve developer experience while collaborating with AI/ML experts and legal specialists.

As a Staff Software Engineer, you'll design scalable backend services, oversee architecture decisions, optimize performance, and enhance CI/CD processes while collaborating with teams.

The role involves leading the design and delivery of a search platform's API and cloud infrastructure, focusing on providing self-service capabilities to internal clients. Responsibilities include API ownership, cloud infrastructure management, reliability engineering, and technical leadership.

The Staff Software Engineer will lead the design and implementation of the ingestion and indexing pipeline for a search platform, ensuring operational health and scalability while leveraging distributed systems and AI technology.

The Senior Applied Scientist will design, build, and deploy AI solutions for document understanding in the legal domain, leveraging NLP and deep learning methodologies. This role involves collaborating with product teams, advancing model capabilities, and ensuring robust training and evaluation methodologies.

The CPQ Lead Solution Engineer will drive engineering strategy and implementation of CPQ solutions, provide technical leadership, collaborate with teams, and ensure system stability.

As Lead Applied Scientist, you will innovate and deliver AI solutions for document understanding, ensuring accountability for research deliverables and optimizing capabilities while guiding technical direction and mentoring team members.

As a Principal Engineer, you will lead AI-driven backend systems for audit products, ensuring scalable, reliable workflows while mentoring teams and influencing technical direction.

The UX Research Ops – Program Manager will lead the design of a research repository and scale AI tools, aligning the research organization towards innovative practices for data access and application.

The role involves building and deploying data infrastructure for AI evaluation systems, establishing data governance standards, driving metric development, and collaborating with cross-functional teams to enhance AI product quality through analytics.