Top AI Jobs in Vancouver

Build and operate AWS serverless platform services that productionize AI/LLM capabilities. Design, implement, deploy, and monitor secure, scalable services, collaborate with AI researchers, maintain CI/CD and observability, and use AI-assisted development tools responsibly.

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.

The role involves architecting AI solutions, optimizing ML systems, and deploying advanced retrieval frameworks. Engineers will lead ML lifecycle from research to production, collaborating across teams to build AI-first products.

Own strategy and roadmap for EviSmart's AI products, define core workflows, instrument feature metrics, drive user validation through interviews and observation, coordinate design transitions, manage competitive positioning, expand into dashboard PLG and mentor the platform PM.

The role involves optimizing AI training and inference systems, focusing on low-precision training, reinforcement learning, and developing software frameworks for AI accelerators to enhance performance and scalability.

Lead enterprise-wide AI transformation, integrating AI into strategy and operations while ensuring measurable business impact across all departments.

Owner of backend implementation and linguistic optimization for TTS in agentic voice agents. Integrate and optimize multi-vendor TTS, apply phonetics and prosody for naturalness, design conversational turns and persona prompts, expose voice parameters to product UI, and collaborate with ASR and Audio AI teams to ensure end-to-end voice quality and low latency.

Design, implement, and maintain gameplay AI systems in Unreal Engine 5. Prototype and integrate AI behaviors for enemies/NPCs, optimize perception, decision-making, navigation, and pathfinding. Integrate AI middleware, establish UE5 engineering best practices, collaborate with design and gameplay teams, and drive performance, maintainability, and production-ready code.

As AI Resilience Fund Manager, you will build and run a fund focused on long-term investments resilient to disruptions caused by AI and economic instability.

The Circuit Analysis Engineer will design, implement, and maintain software for transistor-level circuit simulation using AI frameworks, collaborating with engineering teams.

Build and maintain backend AI capabilities for GitLab Duo Chat: design flow components and agentic flows in Python/LangGraph, integrate LLMs and multi-agent orchestration, implement and maintain APIs in the Rails monolith, improve observability and reliability, and participate in on-call rotations and cross-functional collaboration to deliver safe, scalable AI chat features.

Develop and deliver AI/ML features (LLMs, RAG, agent orchestration) including backend services in Python, integrate cloud services (AWS Bedrock), design knowledge bases and retrieval, improve prompts and agent reliability, review code, write tests and docs, mentor juniors, and participate in architecture and risk management.

Design, build, deploy, and maintain internal AI agents and tools integrated with enterprise systems. Identify AI opportunities, implement governance and security guardrails, monitor costs and performance, research emerging technologies, and enable teams via documentation and training.

Lead design and operationalization of enterprise AI governance: build governance roadmaps, risk frameworks, bias detection/mitigation, and secure-by-design practices. Chair the AI Governance Forum, partner with Cybersecurity, Legal, Privacy and Technology to vet AI solutions, advance AI literacy, and enable safe deployment from PoC to production while growing and mentoring a high-performing team.

Own and evolve Directive's web surfaces for Stratos and company sites: build campaign and reporting UIs, integrate ad/CRM APIs, manage background jobs, containers, CI/CD, databases, telemetry, auth, and LLM integrations; stabilize inherited code and ship production features iteratively.

This role involves optimizing AI systems for large model training and inference, focusing on performance, efficiency, and usability using low-precision training and reinforcement learning techniques.

Lead enterprise-scale transformation to design and implement an AI-enabled global customer support operating model. Define multi-year AI strategy, organizational design, governance, and success metrics. Influence executives and cross-functional partners, drive change management and adoption, translate strategy into measurable roadmaps, and represent transformation outcomes to senior leadership and external stakeholders.

Lead the adoption of AI tools across business functions at EviSmart by mapping workflows, developing training resources, and driving usage within teams.

Design and build AI-powered tools and UI frameworks for Unreal Engine. Own and evolve UI tooling codebase, profile and fix performance/memory issues, mentor engineers, and collaborate across teams to improve developer workflows and support licensees.

Lead enterprise AI strategy and emerging technology adoption across the company. Redesign workflows and operating models, run pilots and scale AI initiatives, build ROI and investment frameworks, partner on governance and risk, and drive organizational adoption and measurable business impact.

Lead finance analytics, own data warehouse and BI strategy, build Finance AI automation and model foundation, optimize GCP costs, create self-service analytics, ensure data governance and audit readiness, and manage a cross-functional team supporting FP&A and accounting.

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.

Conduct AI/ML literature and technology trend research, produce technology reports, evaluate and recommend cutting-edge AI/ML methods, collaborate with cross-functional teams to plan and implement AI projects, and promote innovation and continuous improvement within the AI/ML team.

Lead development of foundation and multimodal models for whole-body MRI, design and validate experiments, drive data quality and annotation standards, apply generative/agentic AI and LLM adaptation, collaborate with clinical and engineering teams, and deliver production-ready, clinically signed models with documented validation and performance benchmarks.

The role involves deep troubleshooting, root cause analysis, and architectural optimization in the Data and AI ecosystem to enhance platform reliability and supportability.