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THE OPPORTUNITY

We are seeking an experienced AI Manager to lead our AI initiatives and ensure compliance with the EU AI Act. The ideal candidate will have a strong background in AI governance, data management, and risk management, along with proficiency in DevOps and ML Ops. This role involves overseeing AI projects, implementing use cases, and managing data governance to drive innovation and efficiency within the organization.

SKILLS AND ATTRIBUTES FOR SUCCESS

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Proven experience in AI governance, data management, and risk management.
• Strong knowledge of the EU AI Act and other relevant regulations.
• Experience in implementing AI use cases and managing AI projects.
• Proficiency in DevOps and ML Ops practices.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work collaboratively with cross-functional teams and stakeholders.
• Fluency in both English and French is a requirement.

PREFERRED SKILLS:

• Experience with AI tools and platforms such as TensorFlow, PyTorch, and Azure AI.
• Knowledge of data privacy regulations and best practices.
• Familiarity with cloud computing and data storage solutions.
• Strong project management skills and experience with agile methodologies.

• AI Governance and Compliance: Ensure all AI systems and processes comply with the EU AI Act and other relevant regulations. Develop and implement AI governance frameworks to maintain ethical standards and regulatory compliance.
• Use Cases Implementation: Identify and implement AI use cases that enhance business operations and customer experiences. Collaborate with cross-functional teams to integrate AI solutions into various business processes.
• Data Governance and Management: Oversee data governance policies and practices to ensure data quality, privacy, and security. Manage data lifecycle, including data collection, storage, processing, and analysis.
• AI Projects Management: Lead and manage AI projects from conception to deployment. Coordinate with stakeholders to define project scope, objectives, and deliverables. Monitor project progress and ensure timely completion.
• DevOps and ML Ops: Implement DevOps and ML Ops practices to streamline AI development and deployment. Ensure continuous integration, delivery, and monitoring of AI models and applications.
• Risk Management: Identify and mitigate risks associated with AI systems and processes. Conduct risk assessments and develop strategies to address potential issues. Ensure AI models are explainable, unbiased, and compliant with regulatory standards.