Top AI Jobs in Ottawa

Drive technical sales and customer success for AI companies, owning implementation and providing effective solutions for usage-based billing.

The Senior AI Engineer position involves building new AI/ML software features, collaborating with teams to understand business needs, and researching innovative AI models.

Lead and manage the MCP and Agentic AI engineering teams, overseeing project execution, technical vision, and team development while integrating AI technologies into products.

The GTM Operations Specialist, AI Automation optimizes AI workflows for Go-To-Market content, manages asset production, and supports cross-functional collaboration for launches and events.

As an AI Application Engineer, build and deploy Agentic AI applications for Fortune 500 companies, analyze customer requirements, and enhance the GenAI performance.

You will be responsible for sourcing exceptional AI talent from consulting firms and universities, building pipelines, assessing candidates, and engaging top performers to join Human Agency.

Build and maintain scalable backend services and APIs, optimize system performance, collaborate with stakeholders, and improve AI workflows.

Build and deploy high-impact AI-native products, architect agent-driven workflows, and collaborate with teams to integrate cutting-edge AI solutions into production systems.

As AI Resilience Fund Manager, you'll establish and manage a fund focused on resilient investments, lead fundraising, and advise investors on navigating challenges created by AI and economic shifts.

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.

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 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.

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

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

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.

Design and optimize ETL processes, build data pipelines with Python, manage Azure solutions, and ensure data integrity for analytics and AI initiatives.

Design and deploy ML solutions for video analytics. Build MLOps pipelines, collaborate on product features, and troubleshoot AI/ML issues.

Provide research and advisory to finance leaders on transforming controllership, AP/AR and financial close using AI and automation. Produce published research, advise on vendor selection, present to clients, and stay current on accounting technology and finance transformation trends.

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.

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

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

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

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