Top AI Jobs in Toronto

The AI/ML Engineering Manager leads ML engineering teams, manages client engagements, shapes architecture, ensures technical quality, and drives business growth through ML operations.

Lead technical direction for agentic AI platforms across AWS/Azure: design architectures, establish standards and governance, ensure secure scalable cloud-native integrations, guide engineering teams, and operationalize AI solutions within a regulated enterprise.

Design and build reusable, metadata-driven data and AI engineering frameworks using Databricks and cloud-native services. Architect and deploy Delta Live Tables, Lakeflow, and orchestrated Databricks workflows for automated data processing and AI agent deployment. Implement RAG/Graph RAG solutions and agent orchestration (AgentOps, Agent-bricks, LangGraph), integrate real-time streams, manage AI agent lifecycles, and ensure governance via Unity Catalog or AWS Glue.

The Senior Principal Researcher will lead AI research initiatives, mentor teams, translate research into scalable systems, and represent Huawei in the global AI community.

The Senior Researcher will develop Physical AI research, focusing on robotic models and multimodal learning while collaborating on experiments and publications.

Design and develop AI agents using large language models, optimize multi-agent systems, and integrate these agents into real-world tools and systems.

Design, build, and iterate on fullstack systems for AI agents. Collaborate with teams to enhance UX and contribute to internal best practices while engaging in research related to AI technologies.

The AI Engineer will design, develop, and deploy AI solutions in property and casualty insurance, focusing on claims processing, underwriting, and customer engagement while ensuring responsible AI practices and effective data integration.

The Chief of Staff will partner with the Managing Director of AI, leading AI transformation initiatives, designing automated processes, and ensuring successful client engagement and organizational rollouts.

Lead end-to-end design of AI-assisted workflows and generated-output experiences for administrators, creators, and learners. Build reusable AI design patterns (review states, approvals, data visibility, recovery, privacy). Rapidly prototype high-fidelity or coded AI behaviors, craft microcopy for AI moments, collaborate closely with Product, Engineering, and AI teams, and perform implementation reviews to ensure polished production experiences.

The Senior Software Engineer will lead the technical roadmap for AI initiatives, architect LLM systems, and mentor engineers while collaborating with product teams to design technical solutions.

The AI/ML Engineer will develop and optimize machine learning models, focusing on conversational systems, multi-agent solutions, and scalability, while collaborating across teams to enhance user experiences.

As a Product Design Intern, you'll design user experiences for AI Agent products, conduct user research, prototype, and collaborate with teams to enhance product strategy and usability.

As a Manager, Applied Research, you will lead a team of scientists to drive innovative AI research into production solutions, mentor team members, and collaborate with product leaders to define AI strategies.

Design and deliver enterprise-grade AI/GenAI solutions on Salesforce or ServiceNow. Lead RAG pipelines, LLM workflows, NLP automation, and vector retrieval integrations. Architect scalable API/microservice integrations, ensure performance, security, and reliability, and define AI governance and guardrails. Collaborate with product, engineering, and customers through discovery, workshops, and demos to operationalize AI for Field and Customer Service workflows.

Manage early-stage grantmaking for the Transformative AI Fund: evaluate applications, recommend grants, source opportunities, support grantees, build partnerships, represent the fund, and develop systems and LLM-assisted tooling to improve grant processes.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Work with founders and the founding team to build AI-powered internal tools and automations, run GTM and community activities, and manage daily operations. Own content, events, scheduling, vendor logistics, and process design while using AI tools to automate and ship solutions.

Lead a Services AI Platform engineering team as a hands-on technical lead: write production-grade Python/Angular code, design multi-tenant agentic ecosystems, build fine-tuning pipelines and RAG retrieval systems, integrate vector and graph databases, enforce clean architectures (MCP servers), and work with SMEs to deploy agent-driven business use cases.

Lead and build shared AI infrastructure and production-grade agents for a product analytics team. Establish repo standards, evaluation tooling, governance compliance, monitor production agents, close data pipeline gaps, and drive adoption across ~35 analysts and 60+ products while interfacing with cross-team AI and data platform partners.

Design, build, deploy, and operate an internal AI platform and AI-powered developer workflows. Implement CI/CD for models, prompts, and evaluations; integrate Bedrock/agent frameworks; ensure security, observability, reliability, and cost/version controls; respond to incidents and participate in on-call rotations; promote AI best practices and lead architecture discussions.

Design Verification Engineer responsible for verifying Tensix IP, building reusable SystemVerilog/Python testbenches and DV infrastructure, developing constrained-random and directed tests, closing coverage, debugging RTL/testbench/workload issues, and integrating CI/CD, simulation/emulation, and containerized regression systems. Collaborates with design, firmware, compiler, and architecture teams.

Lead end-to-end delivery of an AI enablement program: translate strategy into workplans, coordinate cross-functional teams and vendors, manage budgets and risks, maintain program data and reporting, and ensure consistent participant outcomes from intake through impact reporting. Build repeatable systems, run operating cadence, and represent the program to executive and funder stakeholders.

Define enterprise AI strategy and architecture for LLMs, RAG, and predictive models; design secure, high-performance REST/GraphQL APIs and event-driven systems; establish AI/data governance; and lead cross-functional teams to productionize real-time AI applications.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.