Top AI Jobs in Vancouver

Join Welo Data’s contributor network for flexible, remote AI projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Candidates need native or near-native Kannada fluency, English proficiency, digital tool comfort, and strong attention to detail. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s Vietnamese AI contributor network for potential remote projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Projects vary in duration and compensation, with details provided before participation.

Join a remote global contributor network supporting AI data projects. Depending on project needs, you may annotate content, evaluate search results or chatbot responses, create prompts, and verify cultural and linguistic accuracy. Projects range from a few days to several weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s Cantonese AI Trainers Network to support AI data annotation, evaluation, and prompt creation. Work remotely with flexible hours while contributing language and cultural expertise to improve AI systems. Applicants should be native or near-native Cantonese speakers living in Hong Kong, Macau, mainland China, or Malaysia, with strong English skills, digital tool proficiency, attention to detail, and curiosity.

Lead technical pre-sales for AI-enabled content management solutions: run discovery workshops, design scalable cloud and AI architectures, build demos and POCs (LLMs, RAG, LangChain, vector DBs), support proposals and delivery, and mentor teams to integrate AI into managed services for Box, SharePoint, and Blob Storage environments.

Lead full sales cycle for AI-enabled content and automation solutions across Canada and the U.S., focusing on Box, SharePoint, and Blob Storage. Build pipeline, engage senior stakeholders in consultative sales, design solutions with technical teams, manage CRM records, form vendor partnerships, and travel occasionally (up to 25%).

Designs, builds, and deploys production AI solutions for legal and compliance workflows. Partners with legal stakeholders to develop LLM, RAG, agentic AI, document-processing, search, evaluation, governance, security, and compliance applications. Writes tested Python or TypeScript code, manages AI infrastructure and deployment, establishes quality frameworks, and mentors legal users on no-code AI solutions while collaborating with IT and data teams.

Build and operate production AI capabilities, including agent runtimes, model routing, RAG, tool calling, guardrails, evaluation, monitoring, and cost and latency optimization. Develop reliable, measurable, safe AI systems; create evaluation harnesses and quality controls; monitor production behavior; and collaborate with backend, platform, product, and security teams in a client-facing consulting environment.

Leads technical and writing teams delivering generative AI products, coordinating customers, data, product, and research teams. Tracks annotator metrics, manages labeling initiatives, creates prompts and responses, develops stakeholder guidelines, and trains teams on LLM and dataset best practices. The role includes customer interaction, quality assurance, and exposure to potentially toxic or sensitive content.

Lead the development of AI training cluster frameworks and optimization technologies, enhancing efficiency and performance for large model training scenarios.

The intern researcher will optimize AI systems, develop solutions for training and inference, and improve performance on the Ascend platform, focusing on multimodal and reinforcement learning strategies.

The role involves conducting research on AI security, designing LLM approaches for malware classification, and building scalable data pipelines.

Lead advanced AI research projects focused on computer graphics and rendering techniques, mentoring junior engineers and translating ideas into research prototypes.

The role involves leading AI/ML technical planning, evaluating new technologies, collaborating with stakeholders, and fostering innovation in the team.

The Co-op Researcher focuses on AI computing systems, enhancing performance, efficiency, and usability for large model training and inference. Responsibilities include optimization design, building AI clusters, and developing software frameworks for NPU platforms.

Own and operate the delivery platform and embed with an engineering team to improve deployment automation, CI/CD, GitOps, IaC, and production reliability. Lead AI-augmented ops (runbooks, alerting, incident response), build environments, set standards, tune streaming and datastore infrastructure, and mentor teams while tracking DORA and reliability metrics.

Lead strategy and execution for AI-powered customer experience, owning CX AI roadmap, internal AI productivity tools, metrics, and a team. Partner with Product, Engineering, and Data to build, deploy, and iterate AI systems across chat, voice, and email to improve containment, agent productivity, QA automation, and customer outcomes.

Build and maintain backend features for Agent Observability across the GitLab monolith and AI gateway. Design and implement GraphQL/REST APIs, improve automated tests (RSpec), collaborate cross-functionally, troubleshoot production issues on Tier 2 on-call, and help shape responsible AI integration and platform architecture.

Drive customer adoption, implementation, training, and optimization of Glia’s AI products. Advise clients on generative AI, prompt engineering, conversational interactions, and responsible AI practices. Analyze performance metrics, recommend improvements, provide pre-sales consulting, coordinate implementation projects, and communicate client feedback to product and engineering teams.

Lead design, development, and integration of AI/ML features into FortiAnalyzer for security analytics, anomaly detection, and automated response. Manage software developers and data scientists, oversee full ML pipeline (data, training, deployment, optimization), ensure production scalability and security, and collaborate with product, security, and engineering teams.

Design and build an end-to-end AI-governed control plane for release QA: generate spec-driven test plans and cases with LLMs, prioritize and execute tests, automate root-cause analysis and bug lifecycle, and autonomously produce documentation and videos while embedding governance and human oversight.

The Staff Product Designer will craft user experiences for AI-based products, ensuring high-quality execution and collaborating across teams to define future AI UX.

Lead technical architecture and hands-on full-stack development for an AI-powered XR training platform. Define cloud-native solutions, APIs, AI integrations (LLMs, RAG, agents), engineering standards, roadmaps, and mentor developers to deliver scalable, maintainable enterprise-grade software.

Develop experimental AI techniques for agentic marketing applications, especially image and video generation. Build proofs of concept, autonomous evaluation and improvement systems, realistic AI-generated video, and brand-aligned creative generation workflows. The role requires strong quantitative and probabilistic thinking, backend architecture skills, creativity with LLM applications, and product intuition.

Build full-stack web products with substantial LLM functionality, including agentic workflows, tool integrations, structured outputs, and orchestration logic. Translate PRDs and UX mockups into polished prototypes and production systems, making independent product, UX, and technical decisions. Own features through deployment and iteration while collaborating with founders, designers, and stakeholders. Balance rapid AI-assisted development with security, reliability, maintainability, testing, and observability.