Top AI Jobs in Toronto

Embed as financeAI partner across Tax, Controllership, Treasury, FP&A, and Opco teams to identify, prioritize, prototype, and deliver AI and data science solutions. Translate finance problems into technical requirements, ship LLM/retrieval/agentic tools, drive adoption, measure ROI and impact, and help scale the AI finance capability and 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.

Join a research-focused team to integrate AI (LLMs and autonomous agents) into mobile platform development. Build AI-driven code generation and agentic systems, design core mobile components, and collaborate across teams to deploy AI-enhanced developer tooling and monitoring for HarmonyOS and large-scale mobile ecosystems.

Assist in developing and optimizing foundation models, improve training efficiency, and support distributed training and inference systems while collaborating with cross-functional teams.

The role involves designing AI infrastructure, optimizing systems for AI workloads, and collaborating with product teams on innovative cloud solutions.

Build and deploy production LLM/ML pipelines for patent workflows: retrieval, multi-step prompt pipelines, evals frameworks, fine-tuning, agentic workflows, monitoring, and cloud deployment. Collaborate with attorneys and cross-functional teams to convert domain expertise into robust, scalable inference and data solutions.

Lead cross-functional teams to define, build, and deliver production-grade AI/ML solutions. Translate business objectives into technically feasible architectures, drive roadmaps, enforce MLOps and engineering standards, ensure governance and model risk controls, and measure business value from models. Mentor colleagues and coordinate cloud-native deployment, monitoring, and lifecycle management of AI systems.

Lead AI capability strategy and implementation for Salesforce (SFDC). Translate business needs into AI-enabled requirements, design and deliver solutions, run POCs, establish governance, assess vendors, ensure secure scalable integrations, and align cross-functional stakeholders to drive AI-enabled sales productivity and user experience.

Master-level internship to design and deploy agentic workflows and RAG/search pipelines, select and integrate LLMs via APIs/MCP, engineer prompts and evaluations, connect models to data sources, and validate AI-generated outputs within cross-functional teams.

Build and maintain integrations and data pipelines connecting client databases, APIs, and SaaS tools. Extract, clean, transform, and move messy real-world data to feed retrieval and agentic AI systems, apply security and privacy best practices, and document reproducible integrations.

Design, build, and maintain Salesforce-based AI Agents (Agentforce) and intelligent automations. Develop integrations, write and test Apex/JavaScript/Python code, create automated tests, troubleshoot issues, produce technical documentation, support DevOps processes, mentor junior engineers, and collaborate with product and business teams to prototype and deliver AI-driven solutions.

Lead design, development, and maintenance of large-scale Python-based generative AI platforms and services. Collaborate with data science, technical, and business stakeholders to define architecture, deploy GenAI products, enforce coding standards and testing, mentor mid-level engineers, manage multiple projects, and ensure governance, risk, and controls for enterprise-grade AI solutions.

Lead design, development, and deployment of large-scale Python-based Generative AI platforms and services. Drive architecture, stakeholder engagement, vendor partnerships, CI/CD, and governance. Manage multiple complex projects, mentor mid-level engineers, and ensure risk, monitoring, and integration across Citi business units.

Full-cycle technical recruiter for senior, customer-facing AI, cloud, and enterprise architecture roles. Develop sourcing strategies, build diverse pipelines, advise hiring leaders, and deliver data-driven hiring and exceptional candidate experiences in a hybrid environment.

The AI Developer will integrate generative AI into R&D methodologies, develop tools for research tasks, and collaborate with scientists and engineers.

As a Senior Software Engineer at Tenstorrent, you will develop AI compiler technologies, optimize computational graphs, and enhance MLIR frameworks to connect AI models with hardware.

Lead the design and delivery of enterprise agentic automation solutions combining UiPath RPA, AI agents, Microsoft Copilot Studio, Azure AI services, and Power Platform. Define agent logic, HITL workflows, integrations, testing strategies, governance, and operational runbooks. Provide technical leadership, mentor developers, modernize existing RPA, and collaborate with AI, security, and architecture teams to build scalable, secure automation.

Build and operate backend-heavy full-stack applications, APIs, dashboards, and data pipelines. Integrate ML/AI models into production workflows, design data models, containerize and deploy services with Docker/Kubernetes, improve reliability and observability, and collaborate with research, data science, product, and design teams.

The role involves designing and integrating intelligent translation workflows using machine translation, generative AI, and prompt engineering, ensuring compliance and performance optimization.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Lead Moonshot's applied AI safety portfolio, conducting red teaming and adversarial evaluation across online-harm categories, advising AI companies and regulators, managing clients and staff, and growing the portfolio through methodology, business development, and external engagement.

Lead strategy and execution to operationalize AI models across the product portfolio. Define multi-year AI platform and product roadmaps, ensure Responsible AI and regulatory alignment, drive adoption, collaborate cross-functionally, and evangelize outcomes to executives and customers.

Join a VC-backed startup network connecting Director/VP-level AI/ML leaders to portfolio companies. Lead AI strategy, build and scale ML teams, deploy and improve production ML systems, set model quality and responsible AI standards, partner with product and engineering, oversee data and MLOps, evaluate models and tooling, and communicate strategy to executives and boards.

Lead organization-wide quality strategy by embedding shift-left testing, TDD/BDD, and AI-driven validation into CI/CD. Define V&V standards for AI outputs, build automated validation gates and human-in-the-loop checkpoints, evaluate AI developer tools, coach teams, and partner with product to ensure testable acceptance criteria and requirements readiness.