Top AI Jobs in Toronto

Ensure reliability, operability, and controlled enablement of the enterprise AI platform. Administer platform availability, monitoring, incident response, observability, automation, release/change coordination, governance controls, asset visibility, and production readiness. Implement AIOps use cases, maintain telemetry and documentation, and collaborate with engineering, security, and risk teams to meet compliance and operational standards.

Lead AI enablement across workflows and products: evaluate and pilot third-party AI tools, partner with IT and Compliance, co-develop low-code/no-code agents, design testing and rollout plans, create documentation and upskilling collateral, run demos and training, and present actionable recommendations to stakeholders to drive business impact.

Lead technical strategy and execution for Merlin's AI Core platform across perception, sensor fusion, planning, and control. Build and manage a multidisciplinary engineering organization, own architecture from data pipelines to real-time onboard inference, enforce aviation-grade safety and quality, partner with certification and systems teams, recruit senior talent, and translate research into product opportunities.

Build developer tooling, demos, and integrations to enable secure AI agent experiences; contribute to open source; lead architecture, documentation, and cross-functional work to ensure secure, resilient agent-to-service systems.

Partner with customers to architect, build, and deploy high-scale production AI applications. Translate ambiguous goals into reliable, observable services, implement end-to-end model deployment and monitoring, optimize ML projects, and own customer-facing technical delivery and product outcomes.

Develop and deploy generative AI and LLM solutions end-to-end for e-commerce: research models, build ETL/data pipelines, run distributed training and experiments, collaborate with product and engineering to deliver production systems that improve recommendations, search, personalization, and customer interactions.

Build and productionize LLM-powered and agentic AI systems (RAG, fine-tuning, prompt engineering) and web app integrations. Lead design, set best practices, monitor and iterate on performance, mentor engineers, and partner with business and governance to deliver scalable, reusable AI solutions in cloud environments.

Research-focused internship for advanced PhD candidates to develop and evaluate neurosymbolic, knowledge representation, multimodal, and trustworthy AI methods. Duties include defining research questions, building prototypes and benchmarks, running rigorous experiments, collaborating with engineers and domain experts, and moving research toward production and publications.

The Principal AI Platform Engineer will design and maintain infrastructure for GenAI products, ensuring seamless integration and high performance. Responsibilities include implementing security controls, observability solutions, and optimizing scalability.

Support Data Science and Regulatory Affairs to define and execute regulatory strategies for AI/ML-enabled medical devices. Translate ML concepts into regulatory documentation, create DHF and submission materials (510(k), EU MDR, Health Canada), maintain dataset and model documentation, and manage version control and change management.

Founding research hire to develop clinical reasoning and computer-use models using proprietary hospital and clinic data. Own end-to-end training and evaluation pipelines, design benchmarks exposing LLM weaknesses on clinical reasoning, run experiments, and publish technical reports and papers. Collaborate closely with founders and deploy research into products that improve physician workflows.

Design, build, and ship end-to-end AI and data solutions using proprietary data infrastructure. Scope projects with business stakeholders, implement models, pipelines, and APIs (Python/SQL), deploy on Snowflake or BigQuery, and iterate post-launch. Enable non-technical teams, collaborate with Data Engineering and AI teams, and operationalize LLMs, embeddings, and predictive models into working internal products.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Design, build, and operate production multi-agent AI systems and automation for Marketing Operations. Integrate LLMs with business systems (BigQuery, CRMs, Slack), implement RAG pipelines, observability, governance, and scalable serverless/containerized services. Partner with GTM teams to deliver measurable automation and self-service tooling.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

Lead strategy and architecture for GTM and finance systems (Salesforce, NetSuite, Data360/Snowflake, Agentforce). Manage a Salesforce admin, design and operate autonomous Agentforce agents, ensure data governance and a unified customer profile, oversee API integrations and migrations, and build testing and release processes to maintain system integrity and compliance.

The Senior Software Engineer, Voice AI will design and implement complex systems for emergency response communications, oversee AI integrations, and provide technical mentorship.

As an AI Process Forward Deployed Engineer, you will deploy enterprise workflows, improve systems, drive adoption, and collaborate across teams to enhance AI integration in business processes.

Design and build multi-agent AI systems and RAG pipelines, orchestrate LLMs and embeddings, develop scalable full-stack (Node.js/Next.js) APIs, optimize infra (SQL, AWS/GCP, Docker/K8s), lead technical design-to-deployment, ensure code quality, and implement video content classification and tagging for influencer marketing.

Create high-quality video content and integrate AI tools into production workflows, combining storytelling and video craft to enhance cinematic quality.

The Senior Product Manager will drive the AI product roadmap for Revenue Cycle Management, overseeing product lifecycle and collaboration with various teams to enhance billing workflows with AI integration.

Lead AI technical strategy, architect AI systems, set safety standards, mentor engineers, and evaluate AI models at Midi Health, a healthcare-focused company.