ML OPS Engineer

MetLife, Inc.; Galway; On-site; EUR 57,000 - 75,000; Full time

Benefits offered by this job

Hybrid work

Private health insurance

Pension plan

Career development support

Job summary

MetLife Ireland is seeking an experienced ML Ops Engineer to design, build, and operate enterprise ML solutions across the organization. You will bridge Data Science, Data Engineering, DevOps, and Cloud teams to deploy production-grade ML models with robust monitoring and governance.

The role emphasizes CI/CD, automation, and scalable ML platforms, supporting hybrid work arrangements in Ireland. You will collaborate with Data Scientists, Architects, and Information Security to deliver trusted AI

Qualifications

• 5-8 years of IT experience.
• 3+ years in ML Ops, ML engineering, data engineering, or platform engineering.
• Strong understanding of supervised/unsupervised learning and feature engineering.
• Experience deploying ML solutions into production.
• Experience with cloud-native data and AI platforms.
• Experience implementing CI/CD pipelines.
• Strong analytical, with attention to detail and communication skills.

Responsibilities

• Design and implement enterprise ML Ops platforms and frameworks.
• Build reusable ML deployment patterns and automation.
• Develop model serving and inference architectures.
• Create standardised deployment templates and guardrails.
• Support containerisation and orchestration platforms.
• Build and maintain CI/CD pipelines for ML workloads.
• Automate model validation, testing, deployment, promotion and rollback.
• Establish release management standards for ML solutions.
• Ensure auditability, governance, and monitoring of ML models.

Skills

CI/CD pipelines

ML Ops

Cloud platforms

Production ML

Communication skills

Job description

The Opportunity

When you join MetLife’s Global Technology team, you’ll be part of a forward-thinking group dedicated to shaping the future of digital solutions for customers worldwide. You’ll develop, maintain and support technology applications and delivery, leveraging AI, automation, and contemporary ways of working to enhance experiences and drive business outcomes. Your work will simplify complex processes, improve tech resiliency, and ensure high-performing, seamless solutions that power life’s most important moments. In this dynamic environment, you’ll collaborate with talented peers across teams and functions, expanding your skills in impactful ways. Ready to push boundaries and set new industry standards? Join us and help drive the future of technology forward.

MetLife Ireland which is located in both Dublin and Galway City Centres. Dublin is our Operational Headquarters for our Europe Region. In addition, both Dublin and Galway have a significant number of our colleagues that are focused on supporting our broader EMEA and Global functions. They are homes to our Actuarial, Audit, Compliance, Finance, IT, Legal, Operations, Risk and Treasury Teams.

The ML Ops Engineer is responsible for designing, building, automating, deploying, monitoring, and supporting machine learning solutions across the enterprise. The role bridges Data Science, Data Engineering, DevOps, Cloud Engineering, and Architecture teams to ensure machine learning models can be reliably deployed and operated in production.

The candidate will establish and support enterprise ML Ops capabilities, including CI/CD pipelines, model deployment frameworks, feature management, model monitoring, governance controls, and automated retraining processes.

Key Responsibilities

• Design and implement enterprise ML Ops platforms and frameworks.
• Build reusable ML deployment patterns and automation.
• Develop model serving and inference architectures.
• Create standardised deployment templates and engineering guardrails.
• Support containerisation and orchestration platforms.

CI/CD & Automation

• Build and maintain CI/CD pipelines for machine learning workloads.
• Automate model validation, testing, deployment, promotion, and rollback processes.
• Implement Infrastructure-as-Code (IaC) practices.
• Establish release management standards for ML solutions.
• Convert experimental data science solutions into production-grade systems.
• Package, deploy, version, and manage ML models.
• Manage model registries and artefact repositories.
• Support batch, real-time, and API-based inference patterns.

Monitoring & Reliability

Implement monitoring for:

• Operational health
• Establish alerting and observability frameworks.
• Support SLA/SLO compliance for AI and ML services.
• Build and maintain cloud-native ML platforms.
• Manage compute environments for training and inference workloads.
• Optimise platform scalability, performance, reliability, and cost.
• Implement secure access controls and secrets management.
• Ensure compliance with enterprise AI governance standards.
• Support Responsible AI (RAI) requirements.
• Implement auditability, reproducibility, lineage, and traceability controls.
• Maintain model documentation and governance evidence.

Key Stakeholders

• Data Scientists
• Solution Architects
• Information Security teams
• Business stakeholders

Required Qualifications

• 5-8 years of IT experience.
• 3+ years in ML Ops, ML Engineering, Data Engineering, or Platform Engineering.
• Good understanding of supervised learning, unsupervised learning, model evaluation, feature engineering, model life cycle management
• Experience deploying machine learning solutions into production.
• Experience with cloud-native data and AI platforms.
• Experience implementing CI/CD pipelines.
• Strong analytical skills with demonstrated ability to apply analysis to actionable insights
• Excellent verbal and written communication skills with focused attention to details, as well as demonstrated professionalism and time/task management skills

Preferred Qualifications

• Financial Services, Insurance, or highly regulated industry experience.
• Experience supporting enterprise-scale AI platforms.
• Exposure to GenAI, LLMOps, and Agentic AI frameworks.

The expected salary range for this position is €56500 - €75300. This role may also be eligible for annual short-term incentive compensation. All incentives and benefits are subject to the applicable plan terms.

Benefits We Offer

Our Ireland benefits address holistic well-being with programs for physical and mental health, financial wellness, and support for families. We are committed to employee care by delivering comprehensive inclusive offerings and cultivating an environment that drives professional growth, purposeful work, and a supportive culture. Our benefits package includes hybrid work, career development and professional qualification support, full private health insurance for employees and their immediate family members, income protection, defined contribution pension benefits and much more!

About MetLife

Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World’s 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world’s leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East. As part of our New Frontier strategy, MetLife is building an AI-enabled, people-centered future. We’re looking for people who bring curiosity, adaptability, and a growth mindset as we use AI to enhance how we serve customers, support communities, and evolve the way work gets done. At MetLife, AI is a responsible partner that supports human judgment, creativity, and continuous improvement while helping us build trust, inclusion, and long-term value. Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we’re inspired to transform the next century in financial services. At MetLife, it’s #AllTogetherPossible .Join us!