AI Operations Specialist 2

Requirements

• Bachelor's Degree in Computer Science, Engineering, or related field of study.
• 2+ years experience in AI Operations, Machine Learning Engineering, Data Science, Data Engineering, DevOps, Analytics, or related fields, with a focus in retail financial services or information technology fields utilizing agile methodologies.
• 5+ years of experience in AI Operations, Machine Learning Engineering, Data Science, Data Engineering, DevOps, Analytics, or related fields.
• DevOps
• ServiceNow Platform
• Azure Devops
• MLflow
• Apache Airflow
• Application Programming Interface (API)
• Docker (Software)
• GitHub
• Data Analysis
• Microsoft Excel
• Agile Environments
• JIRA Tool
• Reports To : Manager and above
• Direct Reports : 0
• Work Environment
• Normal office environment (Hybrid), 6 to 8 days per month are required in the office.
• Travel
• Ability to travel up to 5% annually
• Other Duties
• About Bread Financial®
• Bread Financial proudly marks 30 years of success in 2026. To learn more about our global associates, our performance and our sustainability progress, visit breadfinancial.com or follow us on Instagram and LinkedIn .
• All job offers are contingent upon successful completion of credit and background checks.
• Bread Financial is an Equal Opportunity Employer.
• Job Family:
• Data and Analytics
• Job Type:
• Regular

Benefits

Additional Information

Every career journey is personal. That's why we empower you with the tools and support to create your own success story. Be challenged. Be heard. Be valued. Be you ... be here. Job Summary The AI Operations Specialist, 2 is responsible for designing and implementing productionized Artificial Intelligence (AI) solutions to solve business problems. This role works closely with our data science teams and other stakeholders to enable the integration of AI/ML models into business processes. These solutions need to be scalable, resilient, and secure. This role also maintains CI/CD pipelines, productionizes models (ML/DL/LLM), and develops integration code needed to deploy AI solutions. Essential Job Functions Design and implement productionized model (ML/DL/LLM) solutions that are scalable, resilient, and secure. Evaluate and optimize data science methodology needs while meeting the non-functional requirements of the business process. Monitor and maintain the performance of deployed models. Monitor production performance and provide recommendations for maximizing ML/LLM configurations and performance. Support tool and platform administrators in maintaining the health and functionality of the ecosystem. Create and manage release pipelines for data science teams that facilitate Continuous Integration (CI), and Continuous Deployment (CD). Automate build and deployment procedures to streamline delivery. Schedule and validate all production deployments. Partner with Release Management, Infrastructure, DevOps, etc. to ensure a smooth and successful deployment. Collaborate with different teams to implement models and monitor outcomes. Provide updates to stakeholders on status of deployments and any risks and issues. Keep up to date with the latest technology trends. Continuously improve models and techniques to adapt to new data patterns and trends.

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