Find work in Canada.

A simpler way to find your next job.

  • Manager - Azure AI Engineering

    Deloitte

    Toronto, ON

    • Full-time
  • AI Architecture Specialist-EN

    CAE

    Montreal, QC

    • Full-time

    Support MLOps and LLMOps practices to enable reliable, repeatable, and scalable AI deployments.

  • GenAI Architect

    Lantern

    Vancouver, BC

    • Full-time

    Experience with MLOps, CI/CD for AI workloads, and responsible AI practices.

  • AI Governance Specialist

    CGI

    Toronto, ON

    • Full-time
  • Generative AI Engineer

    Capgemini

    Toronto, ON · Greater Toronto Area, Canada

    • Full-time

    This is a full time Gen AI Junior Developer working in office in Toronto or Mississauga.

  • AI Software Developer

    Stingray

    Montreal, QC

    • Full-time

    We are currently looking for an AI Software Developer to join our AI team. This position reports to the AI Adoption Leader.

  • Senior Solutions Architect, ISV Canada

    Amazon

    Toronto, ON

    - Experience designing and implementing complex AI/ML solutions, including generative AI, agentic applications, MLOps patterns, and RAG architectures.

  • Data Engineer

    MACLEAN ENGINEERING & MARKETING CO. LIMITED

    Barrie, ON · Collingwood, ON · North Bay, ON · Sudbury, ON

    • $70,000 to $120,000 CAD / year
    • Full-time
  • Senior Consultant - Fraud Analytics

    EY

    Toronto, ON

    Knowledge of MLOps, model governance, explainable AI, and model monitoring practices.

  • AI Engineer

    Pinpoint Global Communications

    Canada

    • Full-time
  • Director, AI & Data Science

    Artefact

    Montreal, QC

    Solid grasp of AI system design: ML model lifecycle (MLOps), agents, tool use, evaluation harnesses, guardrails, and observability.

  • Forward Deployed Engineering, US Oncology

    McKesson

    Mississauga, ON

    • Full-time

    …and work with AI Application Engineering, Data Engineering, MLOps, architecture, security, compliance, and operational teams to transition the solution for industrialization and…

  • Azure Cloud and AI Lead - 69858401

    Cognizant

    Toronto, ON

    • Full-time

    Azure Solutions Architect Expert, Azure Developer Associate, or similar Microsoft Azure certification.

  • Data Scientist

    BNP Paribas

    Montreal, QC

    • Full-time

    Experience with CI/CD pipelines (GIT, Jenkins, …) and MLOps (MLFlow).

  • Solutions Architect

    Shakudo

    Toronto, ON

    • Full-time

    Experience in data engineering, MLOps, or AI infrastructure

  • AI Engineer, Product Analytics

    Thomson Reuters

    Toronto, ON · Canada, Toronto, Ontario

    • Full-time

    Familiarity with MLOps and LLMOps practices and the lifecycle of AI-powered software, including testing, evaluation, and monitoring.

  • Cadre commercial, Services gérés de données et d'IA

    Accenture

    Toronto, ON

    • Full-time

    …modernes des données jusqu'aux opérations de modélisation (MLOps) et aux renseignements disponibles en permanence. Nos équipes aident nos clients à passer d'une prestation basée sur des…

  • Cadre commercial, Services gérés de données et d'IA

    Accenture

    Montreal, QC

    • Full-time

    …modernes des données jusqu'aux opérations de modélisation (MLOps) et aux renseignements disponibles en permanence. Nos équipes aident nos clients à passer d'une prestation basée sur des…

  • AI Architecture Specialist

    CAE

    Montreal, QC

    • Full-time

    Support MLOps and LLMOps practices to enable reliable, repeatable, and scalable AI deployments.

  • GenAI Architect

    Lantern

    Calgary, AB · Edmonton, AB · Vancouver, BC · Toronto, ON

    Experience with MLOps, CI/CD for AI workloads, and responsible AI practices.

  • AI Vision Engineer

    Nexxa.AI

    Remote, Canada

    • Full-time
    • Remote

    Experience with Docker, Kubernetes, and MLOps workflows.

  • Backend AI Engineer

    Nexxa.AI

    Remote, Canada

    • Full-time
    • Remote

    Experience with MLOps tooling: model registries, feature stores, CI/CD for ML, and monitoring/observability for ML systems.