At MetLife, we’re leading the global transformation of an industry we’ve long defined. Founded in 1868, 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 help its individual and institutional customers navigate their changing world. We have operations in more than 40 countries and hold leading market positions in the United States, Japan, Latin America, Asia, Europe and the Middle East.
We are one of the largest institutional investors in the U.S. with $669 billion of total assets under management as of December 31, 2021, ranked #50 on the Fortune 500 list, and honored to have been named to Fortune magazine's list of the "World's Most Admired Companies" for three consecutive years.
MetLife employees are united by purpose, guided by empathy and inspired by one another’s unique backgrounds and perspective to make a difference in the lives of our customers, communities, and the world at large.
With our purpose at our core—Always with you, building a more confident future—sustainability at MetLife means sustaining people’s lives. Sustainability is central to our business strategy and is ingrained across our operations. With the United Nations Sustainable Development Goals (UN SDGs) as a guide, we are deploying the strength of our people, products, services and investments to sustain our customers, our colleagues, our communities and our shareholders.
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.
Role Value Proposition:
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
ML Ops Platform Engineering
- 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.
Model Operationalisation
- 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:
- Model performance
- Data quality
- Data drift
- Concept drift
- Operational health
- Establish alerting and observability frameworks.
- Support SLA/SLO compliance for AI and ML services.
Cloud & Platform Infrastructure
- 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.
Governance, Risk & Compliance
- 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:
Work closely with:
- Data Scientists
- Data Engineers
- Cloud Engineers
- Solution Architects
- Information Security teams
- Business stakeholders
Essential Business Experience and Technical Skills:
Required:
- 5–8 years of IT experience.
- 3+ years in ML Ops, ML Engineering, Data Engineering, or Platform Engineering.
- Experience in Azure ML, Domino, Azure Databricks, ADF
- 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:
- Financial Services, Insurance, or highly regulated industry experience.
- Experience supporting enterprise-scale AI platforms.
- Exposure to GenAI, LLMOps, and Agentic AI frameworks.
MetLife is proud to be an equal opportunity employer. We are committed to attracting, retaining and maximizing the performance of a diverse and inclusive workforce. It is the policy of MetLife to ensure equal employment opportunity without discrimination on any basis protected by law. We welcome applications from candidates of all backgrounds, ethnicities, genders, religions and sexual orientations. We strive to find the best candidate for all positions and a diverse range of applicants ensures we widen our talent pool in order to achieve this. Any applicants with disabilities and neurodiverse conditions, please do let us know about your reasonable adjustments to ensure that we can best meet your needs.
Travel
Negligible
Business Category
Global Technology & Operations
Number of Openings
1
At MetLife, we’re leading the global transformation of an industry we’ve long defined. United in purpose, diverse in perspective, we’re dedicated to making a difference in the lives of our customers.
We ensure to reward and recognise our employees for their contributions and accomplishments at work. We value our employees’ commitment to their work by offering competitive and extensive compensation and benefits package. This includes 25 paid holidays, performance-based bonus, health insurance, income protection and pension benefits. MetLife will also assist in the funding of professional fees for employees where it is relevant and aligned to your position within the organisation. MetLife reserve the right to make a judgement on whether the subscription is relevant or not to your role as well as cease the payment at any time. This type of subscription will not incur “benefit in kind” tax.
Bring your true self to work every day, receive the development and support you need to perform at your best, opportunities to advance your career and surround yourself with like-minded people. Join MetLife.
