Lead AI/ML SRE: Production Reliability & MLOps

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

Job summary

Mastercard is seeking a Lead Site Reliability Engineer (AI/ML) to drive deployment and operation of AI/ML models in production. You will build robust monitoring, collaborate with AI engineers and product teams, and advance MLOps practices to ensure scalable, reliable solutions that deliver business value.

The role emphasizes translating requirements into production-ready pipelines, maintaining data governance and security, and guiding cross-functional initiatives in a fast-paced environment.

Qualifications

• Experience with deploying and managing AI/ML solutions in production.
• Strong understanding of the AI/ML lifecycle from data 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.

Responsibilities

• Lead the E2E deployment and operationalization of AI/ML models and solutions, ensuring they are scalable, reliable, and integrated seamlessly into existing business processes
• Establish and maintain robust monitoring frameworks for deployed AI solutions. Proactively identify performance bottlenecks, data drifts, and other issues, and drive their resolution to ensure optimal business outcomes
• Work closely with business stakeholders, AI Engineers, and product teams to understand business requirements, define success metrics for AI solutions, and ensure deployed models are directly contributing to key business objectives
• Implement and champion MLOps best practices, automation strategies, and efficient workflows to streamline the deployment lifecycle of AI models, from experimentation to production
• Collaborate with risk, compliance, and governance teams to ensure all AI deployments adhere to internal policies, regulatory requirements, and ethical AI principles
• Lead the response to operational incidents related to deployed AI models, conducting root cause analysis and implementing preventative measures

Skills

AI/ML lifecycle

CI/CD for ML

Containerization

Monitoring AI/ML

Cloud platforms

Scripting

Data governance

Data security

Education

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

Tools

Containerization

CI/CD tooling

Job description

Mastercard is seeking a Lead Site Reliability Engineer (AI/ML) to drive deployment and operation of AI/ML models in production. You will build robust monitoring, collaborate with AI engineers and product teams, and advance MLOps practices to ensure scalable, reliable solutions that deliver business value.

The role emphasizes translating requirements into production-ready pipelines, maintaining data governance and security, and guiding cross-functional initiatives in a fast-paced environment.