Top AI Jobs in Toronto

Join Welo Data’s Telugu AI contributor network for potential remote projects involving data annotation, search and chatbot evaluation, prompt creation, and cultural or linguistic quality review. Projects vary in length and compensation, with details provided before participation. Applicants must be based in India, fluent in Telugu and English, comfortable using digital tools, and detail-oriented.

Join Welo Data’s Croatian talent network for potential remote AI projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy reviews. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent community registration rather than an active job opening.

Join Welo Data’s remote Hausa AI contributor network for future projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural accuracy review. This is not an active opening; selected contributors will receive project details, timelines, and compensation when suitable work becomes available.

Join a remote contributor network supporting AI training projects through text, image, and audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Kazakh fluency, English proficiency, digital tool comfort, and strong attention to detail are required.

Join Welo Data’s remote Afrikaans contributor network to support AI training projects through text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with compensation and timelines provided before each assignment. This is a talent-community application rather than an active job opening.

Join Welo Data’s remote Yoruba AI contributor network based in Nigeria. Projects may involve annotating text, images, or audio; evaluating search results, advertisements, or chatbot responses; creating prompts for large language models; and reviewing cultural and linguistic accuracy. Project duration, scope, timelines, and compensation vary. This is a talent community opportunity rather than an active job opening.

Join Welo Data’s Russian-language AI contributor network for flexible, remote projects involving text, image, and audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Contributors are contacted when suitable projects become available and receive project-specific details about tasks, timelines, and compensation.

Join Welo Data’s Basque contributor network for potential remote AI projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent-network opportunity rather than an active job opening.

Join Welo Data’s Canadian English contributor network for flexible, remote AI projects. Potential work includes annotating text, images, or audio; evaluating search results, advertisements, and chatbot responses; creating prompts; and reviewing cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment.

Own the end-to-end product management cycle, including customer discovery, user interviews, solution definition, product requirements, AI prototyping, engineering collaboration, feature launches, and communicating product value. The role focuses on rapidly delivering mobile and web products that improve construction workflows, using data and decisive ownership to address complex customer and operational needs.

Own LanceDB’s product direction by shaping the roadmap with technical leadership, researching users and competitors, gathering continuous user insight, and driving cross-functional prioritization. The role partners closely with engineering as a technically respected peer, defines product changes for AI and data-platform users, uses metrics and experiments to guide decisions, and operates with high ownership in an ambiguous environment.

Build and improve AI-powered customer support agents for telecommunications providers. Responsibilities include developing the agent runtime, configuration tools, observability dashboards, evaluation frameworks, safety guardrails, continuous-improvement systems, and omnichannel integrations across voice, chat, email, and SMS. The role uses TypeScript across frontend, backend, and infrastructure in a serverless microservices environment, with emphasis on LLMs, agent design, product quality, and customer trust.

Supports the development, testing, and maintenance of RESTful APIs, ETL integrations, Power Platform solutions, microservices, and AI-enabled workflows for commercial lending and payments technology. Assists with LLM integrations, intelligent agents, workflow automation, requirements analysis, unit testing, QA triage, documentation, code reviews, incident resolution, and Agile sprint delivery. Collaborates with technical teams, business analysts, project managers, vendors, and IT stakeholders.

Analyze complex structured and unstructured datasets, develop predictive models, apply statistical and machine learning methods, identify data quality issues, and generate actionable insights. The role integrates data from multiple sources, supports modernization and governance initiatives, creates dashboards and analytical frameworks, and communicates findings to technical and non-technical stakeholders. It is hybrid in Toronto with onsite work required five days as project needs dictate.

Lead Data and AI consulting for commercial insurers and reinsurers, advising C-level stakeholders on AI-enabled operating models, transformation strategies, and business capabilities. Drive complex initiatives across underwriting, claims, operations, and distribution from strategy through implementation. Expand the global Data and AI practice through offerings, reusable assets, mentoring, capability building, executive pitches, and business development, while translating GenAI and Agentic AI trends into practical insurance solutions.

Design, build, test, govern, and support AI-enabled solutions across Microsoft Power Platform and Copilot. Develop agents, applications, automations, integrations, and AI services; coordinate testing and UAT; manage security, access, governance, licensing, capacity, and operational support; and partner with business stakeholders through training and adoption. Maintain platform standards, solution inventories, observability, responsible AI practices, and scalable delivery patterns.

Own the enablement strategy and roadmap for a Technical Success organization. Build onboarding, learning journeys, competency models, certifications, labs, and assessments that strengthen technical customer success capabilities. Translate enterprise software architecture, integrations, APIs, and best practices into practical training. Develop customer-facing skills such as discovery, executive communication, consultative conversations, and stakeholder management. Measure proficiency, behavior change, adoption, and business impact while partnering with Product, technical experts, leadership, and Commercial Enablement.

Design, deploy, and operate enterprise AI/ML solutions across AWS, including machine learning pipelines, MLOps, Generative AI, LLMs, retrieval systems, knowledge graphs, and real-time applications. The role requires production software engineering, data engineering, model monitoring, governance, security, and responsible AI expertise. The engineer will partner with stakeholders, lead technical design discussions, influence architecture, and mentor team members while supporting scalable, cloud-native AI services.

Leads AI and digital transformation initiatives by owning product vision and roadmaps, identifying high-impact automation opportunities, ensuring AI governance and compliance, managing adoption and change, and tracking KPIs and ROI. Partners with operations, marketing, customer success, finance, IT, legal, compliance, security, regional teams, patients, and associates to improve digital experiences, operational excellence, competitiveness, and supply-chain workflows.

Reviews and evaluates engineering, infrastructure, and platform documents and work products for technical accuracy, completeness, clarity, consistency, and relevance. Provides structured feedback, identifies errors and gaps, compares technical approaches, and follows defined evaluation frameworks. Requires independent work, strong communication, analytical ability, and professional engineering judgment. The role is fully remote and supports varied technical evaluation projects as an independent contractor.

Lead, coach, and grow a team of UX researchers supporting Stripe Payments and Risk products. Conduct and guide mixed-methods research, translate user insights into product strategy, establish research programs and infrastructure, and enable cross-functional teams to apply research practices. Partner with product, design, business, and executive leaders while guiding AI-driven improvements to research processes and sourcing external research vendors.

Conduct fundamental research in video generation, video editing, and 3D computer vision. Develop state-of-the-art AI and computer vision algorithms, create research prototypes, solve real-world problems, publish in leading conferences, integrate innovations into Huawei products, and supervise interns within collaborative R&D projects.

Lead scientific strategy for foundation models, oversee research excellence, drive innovation, and ensure impactful delivery while building partnerships and advising on AI decisions.

Own the financial services product line from discovery through launch and iteration. Set the roadmap, determine which deployment capabilities become core product features, conduct user discovery, define quality standards, and establish accuracy, human-review, citation, and safe-failure models for regulated workflows. Prototype in design or code, collaborate with engineers and designers, understand the market, and deliver reusable AI capabilities across financial institutions.

Manage the operational delivery of human data for a strategic AI customer. Responsibilities include translating requirements into workflows, managing participant pools and onboarding, tracking supply and quality, leading cross-functional projects, resolving operational issues, documenting processes, and improving scalability with Product and Engineering. The role also supports participant assessment and certification programs while serving as an operational point of contact for delivery teams.