Bank-Jobs in Kanada

We’re building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what’s right for our clients.

At CIBC, we embrace your strengths and your ambitions, so you are empowered at work. Our team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute.

To learn more about CIBC, please visit CIBC.com

We are seeking a leader that can balance vision with execution to a newly formed enterprise machine learning operations (MLOps) team. The Director, Enterprise Machine Learning Frameworks & Operations will lead the design, development, and scaling of our enterprise-wide MLOps capability. This role is critical to establishing AI at scale, driving efficiency, reliability, and compliance across the model development lifecycle—from experimentation to production.

The ideal candidate combines deep technical expertise with strong stakeholder engagement and can execute on a strategic vision. You will contribute to the MLOps strategy, enforce strict adherence to enterprise governance, and lead the implementation of tooling and frameworks to enable secure, scalable, and repeatable AI/ML delivery across the bank. Success will be built on defining the technical activities to mature and standardize the capability and in driving a measurable impact to build influence with stakeholders.

At CIBC we enable the work environment most optimal for you to thrive in your role. You’ll have the flexibility to manage your work activities within a hybrid work arrangement where you’ll spend 1-3 days per week on-site, while other days will be remote.

• Technical Leadership and Contribution: Translate strategic capability roadmaps into actionable technical deliverables, including the design and implementation of CI/CD pipelines, end-to-end MLOps workflows, and automated ML pipelines for data ingestion, training, validation, and deployment. Ensure workflows are compliant with regulatory and enterprise governance requirements, including approval gates, automated monitoring and alerts and audit ready processes. Oversee the development of enterprise-grade, production-ready, and standardized MLOps capabilities to support scalable and reliable AI delivery across the organization. Setting and communicating best practices and guidelines to ensure consistency and high quality delivery
• Stakeholder Management and Collaboration: Build strong relationships and collaborate with business partners, technology teams, and cross-functional stakeholders to gather requirements, prioritize initiatives, and align MLOps solutions with business objectives. Partner with AI governance, Compliance, teams to ensure all solutions adhere to regulatory and internal standards. Participate in code reviews, identify updates to and the need for new documentation and share best practices. Stay current with emerging AI/ML tools and techniques, actively contribute to a culture of experimentation and continuous improvement. Advise on the MLOps strategy and capability roadmap based on stakeholder feedback and emerging needs. Act as the primary point of contact for business and technical stakeholders regarding MLOps delivery.
• People & Culture: Champion a culture of innovation, collaboration and continuous learning within the MLOps team and across the enterprise. Upskill and mentor cross-functional teams on MLOps tools, frameworks, and best practices. Exhibits strong influencing, negotiation, and conflict resolution skills, with the ability to align diverse stakeholders around common goals.

• You can demonstrate 8+ years of experience in software engineering, data platforms, or MLOps, with at least 2 years in a leadership role. Proven track record delivering scalable ML platforms in a highly regulated environment. It’s an asset if you have experience in financial services or other regulated industries.
• You are have relevant knowledge. Deep expertise with cloud-native architecturesand technologies (e.g., Azure ML, Databricks, Kubernetes). Expertise with CI/CD, monitoring, model governance, and observability frameworks. It’s an asset if you have familiarity with responsible AI practices and model interpretability techniques.
• You’re driven by collective success. You have experience partnering with model risk, audit, and data governance teams.
• You have a relevant degree/diploma. Degree in Computer Science, Statistics, Engineering, or a related field.
• Values matter to you. You bring your real self to work and you live our values - trust, teamwork, and accountability.

• We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential. We aspire to give you a career, rather than just a paycheck.
• Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.
• We cultivate a culture where you can express your ambition through initiatives like Purpose Day; a paid day off dedicated for you to use to invest in your growth and development.

*Subject to plan and program terms and conditions

• CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation, please contact Mailbox.careers-carrieres@cibc.com
• You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit.
• We may ask you to complete an attribute-based assessment and other skills tests (such as simulation, coding, French proficiency, MS Office). Our goal for the application process is to get to know more about you, all that you have to offer, and give you the opportunity to learn more about us.

Job Location

Toronto-81 Bay, 16th Floor

Employment Type

Regular

Weekly Hours

37.5

Skills

Artificial Intelligence (AI), Artificial Intelligence Algorithms, Artificial Intelligence Technologies, Cloud Applications, Cloud Computing, Cloud DevOps, Cloud Infrastructure, Data Quality, Data Security, Infrastructure As Code (IaC), Infrastructure Engineering, Microsoft Azure Cloud Services