Top AI Jobs in Vancouver

Design and implement AI systems for team-based sports gameplay in Unreal Engine 5, focusing on decision-making and player behavior optimization, while mentoring other engineers.

Conduct literature reviews and present findings; prototype, develop, and troubleshoot machine learning algorithms for histopathology/medical imaging; maintain AI code repositories and documentation; assist with funding applications and manuscript preparation; oversee project progress and mentor junior staff; present results in meetings and collaborate with internal and external partners.

Lead research on AI-driven systems and networking: develop algorithms and methodologies to improve performance, efficiency, and scalability; collaborate with engineering and product teams; publish and present findings; mentor researchers; and partner with industry and academia to drive system innovation and deployment.

Run strategy and training onboarding sessions, drive customers to first value, manage multiple client cases, own account health and churn prevention, mentor junior teammates, contribute to knowledge base, collaborate with Sales and Enablement, customize onboarding journeys, and identify process improvements to meet KPIs.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, run causal and bandit experiments, decompose merchant economics, and develop agentic deal tooling. Own end-to-end data pipelines, ETL, monitoring, and visualization. Evaluate AI systems for accuracy, bias, and drift, and partner with cross-functional teams to translate results into pricing strategy and automation.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.

Own and improve the AI Social generative media pipeline: build and ship LLM-driven prompts/agent loops, choose and compose media (image, video, voice, music), collaborate with product/design/content, and deliver polished, production-quality social assets.

Lead the design, delivery, and operationalisation of agentic AI workflows and agents from discovery to production. Build integrations with enterprise systems, reusable automation patterns, and monitoring frameworks while partnering with stakeholders and evangelising safe, auditable AI automation across the business.

Design, build, and ship production AI systems for Acquia DAM. Architect agentic, stateful multi-agent workflows, own AI observability and RAG architectures, evaluate LLM providers and tooling, mentor engineers, and ensure enterprise-grade security, scalability, and compliance for AI features.

As a Senior Software Engineer on the AI Platform, you'll develop scalable AI systems, focusing on backend services, workflows, and integrations, partnering with cross-functional teams.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

As Principal Product Manager, you'll define product strategy for GitLab's AI models, focusing on custom and self-hosted AI capabilities, collaborating with engineering, and ensuring alignment with company strategy.

Lead and grow an engineering team for a large-scale SaaS product, providing hands-on technical leadership, code reviews, and architecture guidance. Collaborate with Product and Design to set roadmaps, contribute to implementation, hire and coach engineers, and support career development and team performance. Foster a feedback culture and adapt processes and technology, especially around AI.

As a Senior Data Scientist, you will lead AI risk assessments, coordinate with stakeholders, and ensure effective AI governance practices for safe financial application deployment.

As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.

Lead teams in building end-to-end AI products focused on computer vision and sensor data. Oversee model lifecycle, data management, and deployment. Drive innovation in AI while fostering team development and ensuring customer success.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Lead and own the end-to-end Registry design experience, set vision and KPIs, hire and develop a small design team, use AI-native workflows to prototype and ship cross-platform consumer products, partner with PMs/engineers/analytics, and scale design systems and processes to drive measurable business impact.

As an AI Engineer, you will develop and maintain data pipelines, manage data integration, and enhance data quality for analytics projects.

Lead design and delivery of production autonomous agents and agentic workflows: architect orchestration, integrate and optimize frontier LLMs, drive model fine-tuning and evaluation, mentor engineers, and translate business goals into safe, reliable, scalable AI-powered product experiences.

The Director of Performance Marketing will lead paid marketing strategy, focus on AI integration, manage a high-performing team, and ensure alignment with business objectives.

As a Software Engineer II, you'll develop generative AI applications, enhance sales operations through AI tools, and collaborate with engineering teams on a remote basis.

Lead large-scale, cross-functional engineering projects to deliver AI-native SaaS features. Own platform architecture for multi-tenant, cloud-native systems, drive engineering standards and developer tooling, mentor engineers, and operationalize LLMs, agent frameworks, and real-time data in production.