Top AI Jobs in Vancouver

Conduct applied AI/ML research focused on time-series forecasting and generative AI for supply chain planning. Review literature, formulate hypotheses, design reproducible experiments, develop and evaluate models, analyze results, and communicate findings. Build research prototypes and collaborate with researchers, engineers, data scientists, and domain experts to assess product potential. Contribute to technical reports, demonstrations, publications, and patents under mentorship.

Build and scale 1Password’s Commercial Deal Desk within Revenue Operations. The role partners with Sales, Finance, Legal, and cross-functional teams on complex deals, advising on pricing, terms, discounting, renewals, amendments, and approvals. Responsibilities include reviewing Salesforce CPQ quotes, improving commercial processes and workflows, creating playbooks and training, implementing automation and AI solutions, and using deal data to improve quality, efficiency, and revenue integrity.

Monitors and improves the performance, reliability, and adoption of AI-powered systems. Analyzes operational metrics, develops dashboards and reports, identifies bottlenecks, supports incident resolution, documents procedures, and recommends process improvements. The role collaborates with AI engineers, product teams, business stakeholders, and operations leaders while supporting governance, compliance, risk mitigation, and continuous improvement initiatives.

Leads the strategy, roadmap, development, launch, and optimization of AI-powered products. Defines product requirements, priorities, success metrics, and business outcomes while coordinating engineering, AI, executives, and business stakeholders. Evaluates emerging AI technologies, supports responsible AI governance, manages feedback and adoption, and drives continuous product improvement.

Own AI product backlogs, priorities, user stories, acceptance criteria, and delivery outcomes. Translate business needs into product requirements, collaborate with technical teams on solution design, facilitate stakeholder communication, support Agile delivery, and monitor product performance and adoption. The role also identifies AI-driven improvements, supports product releases, drives continuous improvement, and promotes responsible AI practices.

Translates business needs into AI solution requirements, assesses AI and automation opportunities, develops business cases, and supports solution design and delivery. The role facilitates stakeholder collaboration, testing, implementation, change management, reporting, benefits tracking, and continuous improvement across AI initiatives.

The AI Security Analyst assesses and mitigates risks across AI systems, machine learning platforms, and Generative AI applications. Responsibilities include threat modeling, vulnerability identification, security monitoring, incident response, root cause analysis, access control, policy development, compliance support, audit participation, and secure design reviews. The role partners with engineering, infrastructure, governance, and business teams to improve AI security capabilities and promote responsible AI adoption.

Leads operational oversight, performance analysis, governance, and continuous improvement for AI-powered products and platforms. Develops performance frameworks, executive dashboards, business insights, forecasts, and risk reporting. Partners with engineering, product, and operations teams to improve workflows, support automation, ensure compliance, and drive scalable AI operating models.

Tests and validates AI-powered products, machine learning models, and Generative AI applications. Designs test strategies, executes functional and regression testing, evaluates model outputs, identifies defects, analyzes quality metrics, documents results, verifies compliance, and collaborates with AI engineers and product managers to improve testing practices and release readiness.

Own the backend and agent systems powering LLM products, including multi-turn conversations, tool calling, RAG, state management, evaluations, monitoring, and production reliability. Diagnose failures across models, knowledge systems, tools, and infrastructure; establish regression testing and quality measurement; and guide product and technical decisions. The role requires shipping and improving LLM features at scale, strong backend engineering, disciplined evaluation practices, and preferably Web3 experience.

Build and ship full-stack features, integrations, and enterprise customizations for an open-source AI product. Work directly with technical partners and customers to support deployments, diagnose complex application and infrastructure issues, and convert deployment feedback into reusable product capabilities. Maintain customer-specific solutions, create documentation and runbooks, and collaborate with product and engineering teams on roadmap decisions. The role requires strong judgment, communication, and experience with AI-enabled applications and enterprise deployment environments.

Own Hightouch’s core marketing product portfolio, including audiences, analytics, experimentation, trait building, and orchestration. Set product vision and priorities, lead 0-to-1 innovation, improve adoption, and drive revenue outcomes. The role requires close collaboration with Engineering, Design, executives, customers, and go-to-market teams. This senior, hands-on product leadership position involves managing multiple workstreams, validating market needs, defining MVPs, and presenting product strategy and customer insights.

Lead development of scalable AI platforms and production machine learning services. Design agentic AI capabilities including tool calling, multi-agent systems, planning, reasoning, and human-in-the-loop workflows. Build Python services and Kubernetes-based ML infrastructure, multi-tenant runtimes, data pipelines, and cloud deployments. Apply MLOps, automation, observability, CI/CD, testing, and distributed-systems practices while collaborating with engineers, researchers, and cross-functional teams.

Design, build, and scale an agentic voice AI framework for banking customers. Develop LLM guardrails, grounding, policy enforcement, evaluation, tool-calling, and runtime architecture. Optimize real-time voice latency, maintain production reliability, reduce configuration friction, and collaborate with distributed product and engineering teams. The role also requires strong technical judgment, proactive ownership, AI-assisted development, and leadership through direction-setting, unblocking, and mentorship.

Conducts in-depth legal and business research for attorneys and administrative teams, synthesizes findings, advises on research strategies, manages research projects, and evaluates information resources. Develops training curricula, delivers onboarding, monitors legal-industry developments and emerging AI research technologies, maintains newsletters and intranet content, and recommends resource purchases. Requires expert knowledge of legal and business research platforms, strong communication skills, and the ability to manage competing priorities independently and collaboratively.

Own end-to-end executive and specialized recruiting searches across CSC Generation’s portfolio. Source passive candidates through talent mapping, direct outreach, referrals, and LinkedIn; partner with executives to define roles and sourcing strategies; manage confidential searches; close difficult hires; maintain passive talent pipelines; and provide competitive talent market intelligence.

Own the quality strategy and end-to-end testing pipeline for an AI-generated product handling real-money transactions. Build automated UI, browser, mobile, pre-merge, nightly, release, and production testing gates; integrate testing with CI/CD; evaluate external tools; and improve reliability of critical financial flows. The role partners with engineering and DevOps, uses AI coding agents daily, and drives quality initiatives as an autonomous individual contributor.

Own an AI model domain end-to-end, leading foundation-model and multimodal-system development for whole-body MRI. Design experiments, validation studies, data-quality standards, and clinical reviews; diagnose failure modes; guide generative and agentic AI applications; collaborate across clinical, annotation, engineering, and product teams; and deliver production-ready models with documented validation, clinical sign-off, and performance benchmarks.

Consultative Sales Engineer responsible for driving complex sales opportunities, designing cloud data security and data risk management solutions, delivering proof-of-value engagements and technical demonstrations, advising executive stakeholders, supporting partner channels, and coordinating cross-functional resources. The role requires cloud security, IAM, networking, databases, encryption, privacy, data governance, and strong technical communication skills.

Own AI enablement roadmap workstreams and translate them into engaging learning labs, workshops, office hours, and peer-learning experiences. Facilitate practical use of approved generative AI tools, copilots, agents, and automation while promoting responsible AI adoption. Create learning materials, partner with cross-functional stakeholders and AI champions, manage program delivery, and measure participation, capability, application, adoption, and workflow improvements.

Annotate robot episodes, videos, images, and sensor data for robotics AI models. Label objects, actions, task steps, and outcomes; write behavioral descriptions; identify ambiguous cases; perform annotation quality checks; meet accuracy and throughput goals; and report tool or workflow issues to engineering. The role requires high attention to detail, strong written communication, sound judgment, and comfort working under deadlines and ambiguity.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Build and ship AI-powered internal systems across investing, talent, founder services, finance, and operations. Projects include talent intelligence, sourcing and research tools, diligence workflows, firm knowledge search, operations automation, and reusable portfolio-company AI tools. The role requires end-to-end ownership, from identifying high-leverage problems and selecting the technical stack to building usable products, working with messy business data, and supporting portfolio founders with AI strategy and implementation.

Leads data operations, analytics, merchant and regulatory reporting teams. Owns semantic-layer metric definitions, data governance, BI adoption, reporting accuracy, OKR instrumentation, and data automation. Partners with engineering, data science, product, actuaries, and executives to translate business needs into trusted data solutions. Builds team capability, improves data literacy, and drives cross-functional accountability across technical and business teams.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.