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What you'll be doing
The Director, Enterprise Machine Learning Frameworks & Operations will lead the design, development, and scaling of our enterprise-wide MLOps capability. We are seeking a leader that can balance vision with execution to a newly formed enterprise machine learning operations (MLOps) team. 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.
How you'll succeed
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
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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
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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.
Who you are
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 architectures and 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…
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