Top AI Jobs in Toronto

Designs and owns the production platform powering AI agents and document-processing accelerators. Responsibilities include orchestration, retrieval, model routing, evaluation, observability, inference optimization, reliability, governance, and cost management. The role develops scalable services and APIs, supports legal and regulated workflows, improves system quality and performance, and provides technical leadership through architecture, code reviews, mentoring, and cross-functional collaboration.

Leads BDO’s enterprise Talent Management and Workforce Insights portfolio, including total rewards, people analytics, organizational development, HR operations, and service delivery. Translates people strategy into measurable business outcomes, advances workforce data governance and analytics, modernizes HR processes through technology and AI, and strengthens leadership, organizational effectiveness, performance, wellbeing, and succession. Advises senior leaders, leads specialist teams, and drives integrated, scalable people programs across the firm.

Provides hands-on technical leadership for claims and billing core systems. Responsibilities include architecture, technology roadmaps, scalable and secure solution design, high-severity production issue resolution, AI and agentic AI implementation, emerging-technology research, prototyping, code reviews, and mentoring. The role influences engineering standards and senior technical leaders across the organization while collaborating with architects and executive stakeholders.

Define Auth0’s strategy and architecture for secure AI agents, agentic applications, delegated authorization, and agent-to-resource interactions. Partner across product, engineering, security, customers, and developer communities to shape platform capabilities, standards, and product direction. Build prototypes and reference implementations, advise strategic customers, contribute to standards and open source, communicate technical concepts externally, and mentor teams while addressing identity, authorization, auditability, privacy, and enterprise security.

Optimize software workloads across datacenter and agentic AI applications on RISC-V platforms. Responsibilities include profiling applications and runtimes, identifying bottlenecks, tuning compilers and runtimes, analyzing memory and concurrency behavior, leveraging vector, matrix, and custom ISA capabilities, and developing AI-assisted optimization workflows. The role collaborates across software, compiler, hardware, and performance modeling teams to improve throughput, latency, efficiency, and future CPU architecture.

Generate and qualify inbound and outbound sales opportunities for the Canadian sales team. Research healthcare accounts, engage clinicians and decision-makers, conduct conversations and product demonstrations, diagnose operational pain points, and route qualified opportunities across sales and customer teams. Maintain accurate notes and handoffs, develop strong product knowledge, and continuously improve qualification and messaging processes in a fast-paced, in-person startup environment.

Leads actuarial and data analysts delivering analytics, reporting, monitoring, and explainability solutions. Manages strategic initiatives, workloads, stakeholder relationships, and end-to-end analyses presented to executives and business partners. Provides people leadership through development planning, team engagement, and talent retention while applying SQL, Python, and R to develop innovative analytical solutions. Requires substantial relevant experience and General Insurance expertise.

Own daily operations and quality assurance for an internal AI-powered growth platform. Test releases, rule changes, edge cases, and regressions; document and verify bug fixes; monitor platform and agent activity; manage approval queues; evaluate agent output; escalate risks; and maintain test plans, QA checklists, runbooks, and release notes.

Define the vision, strategy, and roadmap for AI-powered products. Lead use-case evaluation, requirements, experimentation, development, deployment, adoption, and continuous improvement across Generative AI, LLM, RAG, and agentic solutions. Collaborate with engineering, data science, design, and business stakeholders; establish success metrics; manage AI risks; and communicate product value, progress, and strategy to leadership and clients.

Leads GTM data governance, CRM processes, territory and ownership workflows, AI and automation enablement, and MaintainX’s GTM integration into Autodesk. Oversees data quality analysts, defines systems requirements, manages cross-functional programs, establishes AI standards, drives field adoption, and partners with sales, marketing, revenue operations, enablement, engineering, and executive stakeholders to improve productivity and integration outcomes.

Leads the architecture, deployment, and scaling of secure, auditable agentic AI solutions. Partners with executives, clients, industry leaders, and engineering teams to identify use cases, translate business needs into production-ready systems, deploy solutions through AltaForge, establish evaluation standards, and deliver measurable adoption, ROI, and lifecycle value. The role also supports account growth and recurring revenue through successful AI implementation.

Designs, develops, deploys, and optimizes machine learning and deep learning models for customer-facing applications. Responsibilities include experimentation, data analysis, model improvement, production deployment, scalable AI infrastructure, data and training pipelines, cloud integration, and system design. The role also involves applying current research, participating in code reviews, and collaborating with product, design, and engineering teams.

Evaluate AI-generated content in Marathi for linguistic accuracy, naturalness, cultural relevance, and localization quality. Translate English prompts into Marathi, interact with an AI assistant, follow structured evaluation guidelines, and provide consistent, objective feedback. The short-term freelance role requires native-level Marathi fluency, strong English skills, attention to detail, and either relevant education with professional experience or extensive language-related work experience.

Intern will identify productivity challenges and process gaps across global sales teams, prioritize improvement opportunities, and build AI-enabled solutions using Microsoft Copilot, agents, chatbots, Excel automation, and related tools. The role also supports sales process documentation, implementation planning, stakeholder collaboration, governance, and measuring efficiency improvements and business impact.

Own end-to-end analytics engineering for AI and developer experience data. Instrument telemetry, build governed production pipelines, define trusted metrics, and create executive-facing dashboards and analyses. Partner with data engineering, AI, and data science teams to improve data quality and connect raw signals to decision-making. Present clear recommendations on AI investment, developer productivity, and ROI while using AI coding agents to build and maintain pipelines, dashboards, and analyses.

Own end-to-end analytics pipelines for AI usage, developer experience, engineering productivity, and spend. Instrument telemetry, build governed ETL workflows, define trusted metrics, and create executive dashboards and visual narratives. Analyze results, recommend improvements to AI ROI and developer experience, and communicate methodology to senior stakeholders. Collaborate across data engineering, applied AI, and data science while using AI coding agents to build, test, and maintain production data systems.

Build and maintain premium mobile features, subscription and in-app purchase flows, paywalls, pricing experiences, and advertising functionality for Life360’s consumer app. Own feature quality, performance, reliability, experimentation, and incident response at 100M+ user scale. Collaborate with product, design, data science, and analytics teams; use AI coding agents extensively; contribute to architecture and code reviews; mentor engineers; and help evolve AI-native engineering practices.

Build and operate production-grade AI agents that automate workflows across internal teams. Design agent architectures with LangGraph and Amazon Bedrock AgentCore, integrate internal systems and third-party tools, and develop evaluation, observability, and guardrail frameworks. Partner with nontechnical teams to identify workflows, own solutions from prototype through production, measure impact, and drive adoption through documentation and training.

Build and productionize real-time conversational AI systems using voice, chat, LLM orchestration, retrieval, and multi-channel session management. Own services from architecture through Kubernetes/Azure deployment and operations. Develop evaluation infrastructure, tune LLM pipelines for quality, latency, and cost, integrate AI and voice vendors, and establish engineering practices for a growing team. Partner with product and compliance stakeholders to encode domain rules into reliable AI systems.

Design, build, deploy, and optimize scalable AI and machine learning systems using large datasets. Develop predictive models, recommendation systems, personalization engines, forecasting solutions, generative AI applications, and production ML pipelines. Collaborate with data, backend, and product teams to integrate models into applications, while monitoring performance, data quality, drift, reliability, and cost. Establish best practices for evaluation, experimentation, reproducibility, and deployment, and research emerging AI technologies.

Lead AI product strategy and execution across the Merge medical imaging portfolio. Define the AI roadmap, prioritize and launch AI capabilities, establish model governance and monitoring, and reduce time-to-deployment. Partner with engineering, design, clinicians, customers, analysts, and ecosystem partners to deliver governed AI directly into radiology and cardiology workflows. Own success metrics, customer validation, product-readiness reviews, and production delivery of AI/ML-powered products at scale.

Develop, test, implement, document, and support data and AI products. Translate business requirements into technical solutions, contribute to designs, build reusable frameworks and automation, perform regression testing, resolve production issues through root-cause analysis, and improve delivery and deployment processes. The role requires experience with data engineering, ETL/ELT, cloud platforms, structured and unstructured data, AI concepts, GenAI, prompt engineering, RAG, Agile delivery, and JIRA.

Lead the architecture, development, and scaling of data pipelines and infrastructure for a customer-facing Data Lake platform. Build ETL and ingestion systems using GCP, Debezium, Pub/Sub, Dataflow, BigQuery, Python, Golang, and SQL. Establish engineering standards, deliver strategic projects, mentor engineers, influence cross-functional technical decisions, optimize data services, and shape the platform roadmap.

The Legal Technology and AI Attorney applies restructuring expertise to identify, evaluate, and implement AI-enabled tools, automation, knowledge resources, and technology-supported workflows. The role develops templates, playbooks, guidance, and practice-support systems; pilots emerging technologies; trains attorneys and staff; and collaborates with legal, technology, research, and administrative teams to improve efficiency, consistency, and scalability in restructuring matters.

Supports litigation teams by evaluating, configuring, and implementing AI and legal technology workflows. Develops prompts, AI-assisted research and drafting processes, litigation analytics solutions, governance frameworks, training materials, and best practices. Collaborates with attorneys, IT, Information Security, and Knowledge Management to improve document analysis, legal research, case preparation, and technology adoption.