Top AI Jobs in Ottawa

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

Join a Lithuanian-language AI contributor network for flexible remote projects involving 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.

Join Welo Data’s Danish AI contributor network for potential remote projects involving data annotation, content evaluation, search and chatbot quality assessment, prompt creation, and cultural or linguistic accuracy. Projects vary in length and scope, with compensation and details provided before each assignment. Candidates must have native or near-native Danish fluency, English proficiency, digital tool comfort, and strong attention to detail.

Join Welo Data’s Bengali contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertisement, and chatbot evaluation; prompt creation and testing; and cultural or linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each project.

Join Welo Data’s global contributor network for flexible, remote AI projects involving text, image, and audio annotation; search, advertisement, 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 Hebrew, English proficiency, digital tool comfort, and strong attention to detail are required.

Join Welo Data’s Nepali 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 prompts for large language models; and review cultural and linguistic accuracy. Projects vary from several days to 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.

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.

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.

Create hands-on, on-camera educational content teaching AI tools and workflows. Test and evaluate new AI tools, script and record lessons, host live sessions and office hours, provide personalised feedback, and collaborate to build courses, guides, and workshops for a large AI community.

The role involves researching AI/ML concepts for OS, implementing advanced technologies, and optimizing performance and resource management in embedded systems.

The role involves developing AI-based IDE technologies to improve software development efficiency, collaborating on language and compiler capabilities, and prototyping innovations for developers.

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.

Lead and grow an AI engineering organization responsible for delivering enterprise-grade AI applications across business functions. Establish architecture, engineering standards, deployment practices, and technical strategy for scalable AI systems. Mentor engineers, oversee cloud infrastructure, data pipelines, model serving, monitoring, and continuous improvement. Partner with product, data science, and business stakeholders while ensuring security, compliance, governance, reliability, and performance across globally distributed teams.

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.

Build and deploy production GenAI systems, agentic workflows, retrieval pipelines, and data services for enterprise customers. Learn operational domains firsthand, redesign business processes, create evaluation harnesses, write production Python or TypeScript, and deliver observable AWS-based systems. Partner with executives, engineers, and operators to drive adoption and measurable business outcomes while contributing reusable industry blueprints.

Own Aleph’s shared AI foundation, including model selection and routing, proxy infrastructure, context management, tool design, and evaluation systems. Ship production agentic features using prompt engineering, caching, parallel tool calls, and subagents. Build observability for agent performance, collaborate with customers and finance experts to define quality standards, and drive adoption of reliable AI systems across product teams.

Research and optimize AI and machine-learning systems across desktop and mobile platforms. Evaluate model performance, develop and deploy on-device applications and agents, and improve browser ML products. Apply systems and network expertise, collaborate with privacy and security researchers, and investigate AI risks. The role involves open-source development, performance benchmarking, and use of modern ML frameworks to deliver privacy-focused solutions.

Lead the data strategy and own end-to-end data pipelines for AI training, simulation, and deployment in safety-critical autonomous systems. Build data flywheels, integrate with large-scale GPU/TPU training infrastructure, ensure simulator fidelity, partner with safety and certification teams, mentor engineers, and track KPIs for pipeline health and model readiness.

Industry Expert who reviews and defends advanced AI, ML, distributed systems, and forward-deployed engineering projects. Responsibilities include challenging architecture decisions, chairing mock review boards and executive presentations, hosting one or two technical sessions monthly, and serving as the escalation point for instructors. The role requires production-scale engineering judgment, strong technical communication, and expertise in agentic systems, LLM evaluation, infrastructure, observability, model serving, RAG, or enterprise deployments.