Lead AI/ML SRE & MLOps Engineer — Production Excellence

Mastercard; Malahide; On-site; EUR 120,000 - 160,000; Full time

Job summary

Mastercard leads innovation in AI/ML, focusing on translating models from development to production with scalable, reliable deployments and strong governance. The Lead Site Reliability Engineer collaborates with AI engineers and product teams to ensure AI solutions deliver measurable business value and operate efficiently.

The role emphasizes incident response, end-to-end deployment, robust monitoring, and adherence to regulatory and ethical standards across enterprise systems.

Qualifications

• Bachelor's degree or higher in a technical field; strong background in AI/ML operations.
• Minimum 8+ years of experience deploying and managing AI/ML solutions 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 of deployed AI solutions.
• Strong business impact focus and excellent stakeholder communication.

Responsibilities

• Lead end-to-end deployment and operation of AI/ML models and solutions.
• Establish robust monitoring and proactively identify performance bottlenecks and data drift.
• Collaborate with stakeholders and teams to define success metrics and business value.
• Champion MLOps practices and automate deployment lifecycles from experimentation to production.
• Coordinate with risk and governance to ensure compliant, ethical AI deployments.
• Lead incident response and implement preventative measures for AI systems.

Skills

AI/ML lifecycle

CI/CD for ML

Containerization

Scripting

Data governance

Stakeholder management

Communication

Education

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

Tools

Cloud platform services

Monitoring tools

DevOps tooling

Job description

Mastercard leads innovation in AI/ML, focusing on translating models from development to production with scalable, reliable deployments and strong governance. The Lead Site Reliability Engineer collaborates with AI engineers and product teams to ensure AI solutions deliver measurable business value and operate efficiently.

The role emphasizes incident response, end-to-end deployment, robust monitoring, and adherence to regulatory and ethical standards across enterprise systems.