Lead AI/ML SRE — Production Deployment & Reliability

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

Job summary

Mastercard is seeking a Lead Site Reliability Engineer (AI/ML) to drive the deployment, operation, and continuous improvement of AI/ML solutions in production. You will translate models from development to production, ensuring reliability, scalability, and tangible business value across partnerships and platforms.

You will lead end-to-end deployment, establish monitoring, and collaborate with AI engineers, product teams, risk, and governance to uphold compliance and security standards.

Qualifications

• 8+ years of experience in AI/ML operations, MLOps, DevOps or related role.
• Experience deploying and managing AI/ML solutions in production environments.
• Solid understanding of AI/ML lifecycle from data prep to deployment and monitoring.
• Familiarity with cloud AI/ML services and platforms.
• Proficiency in scripting and containerization technologies.
• 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.
• Establish and maintain robust monitoring for deployed AI solutions; identify performance bottlenecks and data drifts.
• Collaborate with business stakeholders, AI engineers, and product teams to define success metrics.
• Implement and champion MLOps practices, automation and efficient deployment workflows.
• Ensure AI deployments comply with risk, governance and regulatory requirements.
• Lead incident response and root-cause analysis for AI model issues.

Skills

AI/ML lifecycle

Cloud platforms

Scripting

Containerization

CI/CD for ML

Monitoring AI/ML

Data governance & security

Education

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

Job description

Mastercard is seeking a Lead Site Reliability Engineer (AI/ML) to drive the deployment, operation, and continuous improvement of AI/ML solutions in production. You will translate models from development to production, ensuring reliability, scalability, and tangible business value across partnerships and platforms.

You will lead end-to-end deployment, establish monitoring, and collaborate with AI engineers, product teams, risk, and governance to uphold compliance and security standards.