AI ModelOps Engineer

Posted Yesterday
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Toronto, ON, CAN
In-Office
80K-131K Annually
Entry level
Retail
The Role
Designs, operates, and improves enterprise AI and MLOps platforms supporting machine learning models, generative AI, LLMs, and AI agents. Responsibilities include deployment, monitoring, governance, lifecycle management, observability, automation, CI/CD, infrastructure provisioning, security, reliability, and cost optimization. The role collaborates with data scientists, engineers, architects, and business stakeholders while developing platform standards, reusable components, evaluation frameworks, and operational processes for scalable AI adoption.
Summary Generated by Built In

As an AI ModelOps Engineer, you will be part of the Enterprise AI Platforms & AI ModelOps team within the AI and Data group at Canadian Tire Corporation (CTC). In this role, you will support the infrastructure and provisioning of environments that enable our AI teams to build and deploy agentic AI solutions. You will help design, implement, operate, and optimize the platforms, tools, and processes that support AI solutions across their lifecycle. You will contribute to the evolution of CTC's AAAI platform and MLOps ecosystem, enabling the development, deployment, monitoring, and governance of machine learning solutions at scale. In parallel, you will help establish and mature CTC's Agentic AI platform capabilities, including support for generative AI, large language models (LLMs), AI agents, agentic workflows, and emerging AI engineering practices. Through automation, observability, governance, and platform engineering, you will help accelerate the secure and responsible adoption of AI technologies across the enterprise.

You will play a key role in operating, enhancing, and scaling the platforms and services that underpin CTC’s AI ecosystem. This includes enabling the reliable deployment, monitoring, governance, and lifecycle management of machine learning models, generative AI solutions, and AI agents in production environments. You will evaluate, implement, and support modern AI engineering capabilities, including observability, automation, model and agent registries, evaluation frameworks, and platform integrations that accelerate the adoption of enterprise AI solutions. Working closely with data scientists, AI engineers, cloud engineers, architects, and IT teams, you will ensure the stability, reliability, security, and performance of AI platforms while driving operational excellence through automation, continuous improvement, and platform innovation.

What you'll do

  • Design, implement, operate, and continuously improve the platforms, tools, and processes that support the end-to-end lifecycle of AI solutions across the enterprise.

  • Enable the deployment, monitoring, governance, and lifecycle management of machine learning models, generative AI solutions, and AI agents in production environments.

  • Contribute to the evolution and operational excellence of CTC's AAAI platform and MLOps ecosystem, ensuring scalability, reliability, security, and performance.

  • Help establish and mature Agentic AI platform capabilities, including infrastructure, platform services, tooling, integrations, registries, observability, evaluation frameworks, and operational processes.

  • Develop and maintain automation, CI/CD pipelines, and platform services that accelerate the delivery, validation, deployment, and operation of AI solutions.

  • Design and implement observability, monitoring, alerting, and troubleshooting capabilities to ensure the health, reliability, and performance of AI platforms and workloads.

  • Collaborate with data scientists, AI engineers, cloud engineers, architects, software developers, and IT teams to operationalize AI solutions and promote engineering best practices.

  • Evaluate, recommend, and implement emerging AI platform technologies, tools, frameworks, and engineering practices that enhance platform capabilities and accelerate business value.

  • Support platform governance initiatives, including model and agent lifecycle management, auditability, operational controls, compliance requirements, and responsible AI practices.

  • Contribute to the development and adoption of platform standards, reusable components, reference architectures, templates, libraries, and best practices for AI engineering and operations.

  • Ensure the availability, scalability, resilience, security, and cost efficiency of AI platform infrastructure through proactive capacity planning, operational readiness, and continuous improvement initiatives.

  • Perform post-deployment analysis and operational reviews to identify optimization opportunities and improve platform reliability, efficiency, and user experience.

  • Partner with enterprise stakeholders to drive the adoption and effective use of AI platforms, services, and capabilities across CTC.

  • Stay current with industry trends and advancements in machine learning, generative AI, Agentic AI, cloud platforms, and AI engineering, providing recommendations for continuous platform evolution.

What you bring

  • Hands-on experience with MLOps, GenAI operations, or AI platform engineering, including model deployment, monitoring, observability, automation, and lifecycle management.

  • Experience building and operating AI, machine learning, or data platforms in cloud environments, preferably Microsoft Azure.

  • Strong understanding of machine learning concepts, model lifecycle management, model governance, and operational best practices.

  • Experience with generative AI technologies, large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and emerging AI engineering practices.

  • Proficiency in Python and experience developing, integrating, and supporting AI-enabled applications and services.

  • Experience with AI development and operational platforms such as Azure AI Foundry, Azure Machine Learning, Databricks, MLflow, or similar technologies.

  • Experience implementing monitoring, logging, alerting, observability, and performance management solutions for production AI workloads.

  • Experience with containerization and cloud-native technologies, such as Docker, Kubernetes, and related orchestration platforms.

  • Familiarity with DevOps and platform engineering practices, including CI/CD pipelines, source control, automation, and Infrastructure as Code (IaC).

  • Practical experience with Infrastructure as Code tools such as Terraform, Bicep, or equivalent technologies.

  • Knowledge of cloud security, governance, access management, compliance, and responsible AI practices.

  • Strong understanding of system reliability, scalability, resiliency, troubleshooting, and root cause analysis.

  • Excellent verbal and written communication skills, with the ability to collaborate effectively across technical and business teams.

  • Ability to lead technical discussions, architecture reviews, workshops, demonstrations, proofs of concept, and platform enablement activities.

  • Ability to communicate complex technical concepts to both technical and non-technical stakeholders.

  • Strong relationship-building, stakeholder management, and influencing skills.

  • Demonstrated curiosity, adaptability, and commitment to continuous learning in a rapidly evolving AI landscape.

  • Ability to work independently and collaboratively in a fast-paced, cross-functional environment.

  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline, or an equivalent combination of education, certifications, and practical experience.

 

We’re always looking for great talent! In addition to competitive pay, we offer:

  • Comprehensive benefits and retirement programs

  • Performance incentives, Continuing Education Programs

  • Other perks to support your well-being

  • Career growth opportunities and product discounts

Our typical hiring range is between $80,000.00 and $131,000.00 per annum. Salary decisions are also dependent on other factors such as your experience, job-related knowledge, skills and competencies, market location, industry benchmarks, internal equity and other role-specific requirements. We're committed to attracting top talent.  For critical roles, the compensation offering will be reviewed to ensure alignment with market rate and conditions and the unique value you bring to the role. #LI-AG2

This posting represents an existing vacancy within our organization.

We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters.


About Us


Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, over 1,600 retail locations, financial services, exemplary e-commerce capabilities, and exciting market-leading merchandising strategies. We dream big and work as one to innovate with purpose for our customers at every level of our business, investing in new technologies and products, and doubling down on top talent to drive the company forward. We offer competitive salaries and wages to CTC employees, as well as store discounts, supported learning through our Triangle Learning Academy, Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees. As part of our enhanced flex benefits program, we offer mental health benefits in the amount of $5,000 per year for benefits-eligible employees and their families, including total well-being, and mental health tools and resources for all employees. Join us in helping to make life in Canada better through living and working our Core Values: we are innovators and entrepreneurs at our core, outcomes drive us, inclusion is a must, we are stronger together and we take personal responsibility. It is an especially exciting time to join CTC and its family of companies where career opportunities are wide-ranging! Join us, where there's a place for you here.


Our Commitment to Diversity, Inclusion and Belonging 


We are committed to fostering an environment where belonging thrives, and diversity, inclusion and equity are infused into everything we do. We believe in building an organizational culture where people are consistently treated with dignity while respecting individual religion, nationality, gender, race, age, perceived ability, spoken language, sexual orientation, and identification. We are united in our purpose of being here to help make life in Canada better.


Accommodations  


We stand firm in our Core Value that inclusion is a must. We welcome and encourage candidates from equity-seeking groups such as people who identify as racialized, Indigenous, 2SLGBTQIA+, women, people with disabilities, and beyond. Should you require any accommodation in applying for this role, or throughout the interview process, please make them known when contacted and we will work with you to help meet your needs.


Skills Required

  • Hands-on experience with MLOps, GenAI operations, or AI platform engineering, including model deployment, monitoring, observability, automation, and lifecycle management.
  • Experience building and operating AI, machine learning, or data platforms in cloud environments.
  • Strong understanding of machine learning concepts, model lifecycle management, model governance, and operational best practices.
  • Experience with generative AI technologies, large language models, retrieval-augmented generation, AI agents, and emerging AI engineering practices.
  • Proficiency in Python and experience developing, integrating, and supporting AI-enabled applications and services.
  • Experience with Azure AI Foundry, Azure Machine Learning, Databricks, MLflow, or similar AI development and operational platforms.
  • Experience implementing monitoring, logging, alerting, observability, and performance management solutions for production AI workloads.
  • Experience with containerization and cloud-native technologies such as Docker and Kubernetes.
  • Familiarity with DevOps and platform engineering practices, including CI/CD pipelines, source control, automation, and Infrastructure as Code.
  • Practical experience with Infrastructure as Code tools such as Terraform, Bicep, or equivalent technologies.
  • Knowledge of cloud security, governance, access management, compliance, and responsible AI practices.
  • Strong understanding of system reliability, scalability, resiliency, troubleshooting, and root cause analysis.
  • Excellent verbal and written communication skills and ability to collaborate across technical and business teams.
  • Ability to lead technical discussions, architecture reviews, workshops, demonstrations, proofs of concept, and platform enablement activities.
  • Ability to communicate complex technical concepts to technical and non-technical stakeholders.
  • Strong relationship-building, stakeholder management, and influencing skills.
  • Curiosity, adaptability, and commitment to continuous learning in a rapidly evolving AI landscape.
  • Ability to work independently and collaboratively in a fast-paced, cross-functional environment.
  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent education, certifications, and practical experience.
  • Microsoft Azure cloud experience.
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The Company
HQ: New York, NY
9,112 Employees

What We Do

HBC is a diversified global retailer focused on driving the performance of high quality stores and their omni-channel offerings and unlocking the value of real estate holdings. Founded in 1670, we are the oldest company in North America.

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