AI/ML SRE Lead: Deploy & Scale AI Solutions

Mastercard; Celbridge; On-site; EUR 120,000 - 180,000; Full time

Job summary

Mastercard seeks a Lead Site Reliability Engineer (AI/ML) to drive deployment, operations, and continuous improvement of AI/ML solutions. You’ll translate models from development to production while ensuring reliability and measurable business value.

In this role you’ll build scalable monitoring, collaborate with AI engineers, product teams, and governance, and lead incident response. A strong background in AI/ML lifecycle, cloud platforms, and MLOps is required.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Business, or a related field.
• 8+ years of experience in AI/ML operations, MLOps, DevOps or related role deploying/managing AI/ML in production.
• Solid understanding of AI/ML lifecycle from data prep to deployment and monitoring.
• Experience with cloud platforms and their AI/ML services.
• Proficiency in scripting and familiarity with containerization technologies.
• Knowledge of CI/CD pipelines for ML models and monitoring tools for AI/ML.
• Understanding of data governance, data quality and data security in AI/ML.

Responsibilities

• Lead end-to-end deployment and operationalization of AI/ML models and solutions, ensuring scalability and reliability.
• Establish robust monitoring frameworks; identify performance bottlenecks and data drifts; drive resolutions.
• Collaborate with business stakeholders, AI Engineers, and product teams to define success metrics and ensure models meet business objectives.
• Implement MLOps best practices, automation, and efficient workflows across the deployment lifecycle.
• Coordinate with risk, compliance, and governance teams to adhere to policies and ethical AI principles.
• Lead incident response for AI models, perform root-cause analysis, and implement preventative measures.

Skills

AI/ML lifecycle

Cloud platforms

Scripting

Stakeholder management

Business impact

Communication

Cross-functional leadership

Operational excellence

Incidents & root cause analysis

Data governance & security

Education

Bachelor's degree in Computer Science, Engineering, Data Science, Business, or related field

Tools

Containerization technologies

CI/CD pipelines for ML

Monitoring tools for AI/ML

Job description

Mastercard seeks a Lead Site Reliability Engineer (AI/ML) to drive deployment, operations, and continuous improvement of AI/ML solutions. You’ll translate models from development to production while ensuring reliability and measurable business value.

In this role you’ll build scalable monitoring, collaborate with AI engineers, product teams, and governance, and lead incident response. A strong background in AI/ML lifecycle, cloud platforms, and MLOps is required.