Top AI Jobs in Ottawa

The Experience Design Architect will lead the development of AI-powered experiences, drive strategy, mentor designers, and influence stakeholders across organizations.

The Engineering Manager leads backend engineers to develop AI simulation platforms, driving technical strategy and fostering a culture of continuous growth while ensuring project goals align with R&D efforts.

Lead sales efforts for AI solutions at Labelbox, developing relationships with top AI labs and Fortune 500 companies, managing the sales cycle and ensuring client satisfaction.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

The AI Engineer role involves optimizing language models for fraud detection and building backend infrastructure to support scalable operations for risk management and as well as developing efficient machine learning solutions.

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.

The Senior AI Engineer will lead AI project architecture, build AI solutions, integrate systems, and promote MLOps best practices while collaborating with teams to apply AI in business contexts.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

Responsible for developing and deploying AI/ML models, integrating systems, optimizing LLM performance, and implementing MLOps practices within GCP.

The Lead Product Manager, AI will identify and build AI-powered products, drive growth and customer experience, and collaborate with cross-functional teams.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

The AI Enablement Engineer leads programs for engineering teams to integrate AI, teaches best practices, and develops scalable learning models.

The Product Manager will evaluate and manage relationships with LLM models, define product strategy, and coordinate cross-functionally to enhance customer experience while driving product roadmap and adoption.

The Staff Software Engineer will lead architectural modernization, collaborate across teams, develop proofs of concept, mentor engineers, and ensure technical excellence in delivering high-quality software solutions.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

Manage AI and ML solutions, leading model development and deployment while mentoring engineers and collaborating with cross-functional teams.

Lead business development and strategy for AI infrastructure, focusing on cloud compute buyers and establishing strategic partnerships in the technology ecosystem.

The AI-First Data Scientist will design and deploy ML solutions, conduct causal analysis, and partner with business leaders to drive AI integration into decision-making.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

Lead the fullstack development of Glean's Generative AI products, managing and mentoring engineers while driving product improvements and team growth.

Lead complex content strategies for digital ecosystems, addressing user needs and business goals through scalable architecture and governance models. Collaborate across teams, conduct audits, and advise on AI capabilities, ensuring clarity and effectiveness in content systems.

Lead a team of data scientists and AI engineers to deliver AI-driven solutions and drive business impact through innovation and collaboration.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The role involves designing and maintaining infrastructure for machine learning applications, deploying ML pipelines, optimizing resources on GCP, and ensuring system observability.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.