Top AI Jobs in Toronto

Lead modernization of month-end and year-end close processes using AI and automation. Prepare, review, and validate journal entries, accruals, and financial statements. Implement anomaly detection, automated reconciliations, variance analysis, and predictive insights. Collaborate with data teams to structure finance data for ML use cases and design audit-ready, scalable reporting workflows.

Manage and optimize end-to-end account reconciliations, intercompany eliminations, and chart-of-accounts governance. Identify discrepancies, perform variance analysis, and implement AI-driven automation and anomaly detection to reduce manual effort and accelerate close. Collaborate with cross-functional teams to resolve mismatches and improve financial data quality and reporting accuracy.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

Design realistic, specialty-specific clinical case scenarios and gold-standard attending-level responses, evaluate and grade AI-generated outputs using structured rubrics, provide detailed written feedback to improve model clinical reasoning, and participate in onboarding, calibration, and review sessions in a fully remote, asynchronous contractor role (~20 hours/week).

Design, build, and optimize high-performance AI infrastructure systems to support intelligent agents, ensuring reliability and scalability for millions of users.

Lead engagement strategy and roadmap for Life360’s member experience, setting multi-quarter direction, defining engagement metrics, partnering with Growth and Platform, running experiments at multiple scales, shipping end-to-end experiences, and operating as an AI-native product manager to drive frequency, multi-circle participation, and durable MAU.

Lead Life360's Data Engineering organization and own end-to-end data platform and analytics engineering strategy. Define architecture for ingestion, transformation, modeling, and serving data for humans and LLMs. Manage engineering managers and teams, drive self-serve data capabilities, cost management, vendor decisions, data quality/governance, and partner cross-functionally to prioritize engineering work that drives business impact.

Own supply and demand partnerships for Pyth Pro: onboard tier-1 market makers and data publishers, build enterprise pipelines with AI firms and institutional buyers, close complex $1M+ deals, develop GTM playbooks for the US institutional AI market, represent the product at industry events, and shape incentive and commercial models to scale adoption.

Lead product development for Maestro, an AI platform for mortgage origination and servicing. Translate operational workflows into PRDs, define metrics (throughput, time-to-decision, accuracy), collaborate with ML, engineering, underwriting ops, and stakeholders, build feedback loops between AI output and human judgment, and drive roadmap execution in a regulated, high-ambiguity environment.

Build production-ready backend components that interface directly with LLMs, create tooling to automate LLM-in-the-loop testing, design and validate LLM-based solutions using real biomedical data, and develop metrics to measure model performance and reliability under production load.

The Sales Strategy and Operations Manager leads complex sales opportunities, develops ROI models, engages executives, and coordinates cross-functional input for compelling proposals.

As a Staff Backend Engineer, you'll lead the architecture and development of AI features, mentor engineers, and ensure system reliability and scalability within an event-driven microservices environment.

The AI Operations Specialist will support CoinMarketCap's AI team by conducting feature evaluations, developing tools and automations, managing outreach, and collaborating with internal stakeholders to enhance AI operations.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

Design and build conversational AI agents for customer service, ownership of agent systems from architecture to production, and implement safety and evaluation frameworks.

As a Full Stack Engineer, you will build AI-powered applications, manage client interactions, and apply best practices in MLOps and LLMOps.

The Solution Architect designs AI solutions that automate workflows, collaborates with stakeholders, and integrates systems, ensuring continuous improvement and deployment.

As an Engineering Manager, you'll build and lead a high-performing engineering team focused on AI product innovations while collaborating with cross-functional teams to enhance customer experiences through automated audit processes.

Lead engagement with business teams to develop AI-driven internal applications, managing everything from discovery to production and ensuring high adoption post-launch.

The AI Enablement Lead will design and conduct training programs to improve AI fluency within Juniper Square, focusing on tools like Claude and Cowork. Responsibilities include curriculum development, leading sessions, coaching, and measuring adoption outcomes.

The Senior Software Engineer will design and build AI workflows, optimize features, collaborate across development phases, and mentor other engineers, focusing on fullstack development and SaaS products.

The Senior AI/ML Engineer will develop AI systems for enterprise decision-making, focusing on LLMs and real-time data processing. Responsibilities include building detection systems, insight engines, evaluation frameworks, and collaborating with engineers to ensure robust AI product engineering.

As Co-Founder & CPTO, you will direct product and engineering, oversee architecture and AI model development, and drive customer engagement and fundraising efforts.

As Co-Founder & CTO, you will lead product and engineering, ensure production reliability of AI systems, and grow the founding team, focusing on transitioning from pilots to paying customers.

The AI Enablement Lead will drive AI adoption across the company, build AI agents and automations, and enhance teams' capabilities with AI tools while tracking adoption and productivity metrics.