Lead Site Reliability Engineer (AI/ML)

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

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Lead Site Reliability Engineer (AI/ML)

As a Lead Site Reliability Engineer at Mastercard, you'll play a pivotal role focusing on the seamless deployment, operationalization, and continuous improvement of our AI/ML solutions. You'll be instrumental in translating AI models from development to production, ensuring they deliver tangible business value, operate efficiently, and meet key performance indicators.

Key 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

Qualifications

• Education: Bachelor's degree in Computer Science, Engineering, Data Science, Business, or a related field
• Experience: Minimum of 8+ years of experience in AI/ML operations, MLOps, DevOps, or a related role with a strong focus on deploying and managing AI/ML solutions in production environments.
• Technical Skills:
  • Solid understanding of the AI/ML lifecycle, from data preparation and model training to deployment and monitoring.
  • Experience with one of the cloud platforms and their AI/ML services
  • Proficiency in scripting and
  • Familiarity with containerization technologies
  • Knowledge of CI/CD pipelines for machine learning models.
  • Experience with monitoring tools for AI/ML solutions
  • Understanding of data governance, data quality, and data security principles relevant to AI/ML
• Strong ability to understand business needs, translate them into technical requirements for AI solutions, and articulate the business value of AI deployments
• Excellent communication, interpersonal, and stakeholder management skills
• Ability to effectively bridge the gap between technical and business teams
• Demonstrated ability to lead initiatives, drive cross-functional projects, and influence outcomes without direct authority
• Strong understanding of operational processes and a passion for optimizing them

Corporate Security Responsibility

• Abide by Mastercard’s security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines