{"id":4245725,"url":"https://alion.io/job/metlife-ml-ops-engineer","title":"ML OPS Engineer","company":{"id":450553,"name":"MetLife","domain":"metlife.com","url":"https://alion.io/company/metlife-5","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Galway, Ireland"],"countries":["IE"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":56500,"max":75300,"currency":"EUR","period":"year","gross":null,"usd_annual":83253},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"AI Agents","optional":true},{"name":"LLMOps","optional":true}],"status":"live","first_seen_at":"2026-11-13T12:33:39Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-14T01:11:18Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"The Team You Will Join\nWhen 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.\nMetLife 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.\n\nThe Opportunity\nThe 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.\nThe 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.\n\nKey Responsibilities\nML Ops Platform Engineering\nDesign and implement enterprise ML Ops platforms and frameworks.\nBuild reusable ML deployment patterns and automation.\nDevelop model serving and inference architectures.\nCreate standardised deployment templates and engineering guardrails.\nSupport containerisation and orchestration platforms.\nCI/CD & Automation\nBuild and maintain CI/CD pipelines for machine learning workloads.\nAutomate model validation, testing, deployment, promotion, and rollback processes.\nImplement Infrastructure-as-Code (IaC) practices.\nEstablish release management standards for ML solutions.\nModel Operationalisation\nConvert experimental data science solutions into production-grade systems.\nPackage, deploy, version, and manage ML models.\nManage model registries and artefact repositories.\nSupport batch, real-time, and API-based inference patterns.\nMonitoring & Reliability\nImplement monitoring for:\nModel performance\nData quality\nData drift\nConcept drift\nOperational health\nEstablish alerting and observability frameworks.\nSupport SLA/SLO compliance for AI and ML services.\nCloud & Platform Infrastructure\nBuild and maintain cloud-native ML platforms.\nManage compute environments for training and inference workloads.\nOptimise platform scalability, performance, reliability, and cost.\nImplement secure access controls and secrets management.\nGovernance, Risk & Compliance\nEnsure compliance with enterprise AI governance standards.\nSupport Responsible AI (RAI) requirements.\nImplement auditability, reproducibility, lineage, and traceability controls.\nMaintain model documentation and governance evidence.\nKey Stakeholders:\nData Scientists\nData Engineers\nCloud Engineers\nSolution Architects\nInformation Security teams\nBusiness stakeholders\n\nRequired Qualifications\n5-8 years of IT experience. \n3+ years in ML Ops, ML Engineering, Data Engineering, or Platform Engineering. \nExperience in Azure ML, Domino, Azure Databricks, ADF \nGood understanding of supervised learning, unsupervised learning, model evaluation, feature engineering, model life cycle management \nExperience deploying machine learning solutions into production. \nExperience with cloud-native data and AI platforms. \nExperience implementing CI/CD pipelines. \nStrong analytical skills with demonstrated ability to apply analysis to actionable insights\nExcellent verbal and written communication skills with focused attention to details, as well as demonstrated professionalism and time/task management skills\n\nPreferred Qualifications\nFinancial Services, Insurance, or highly regulated industry experience.\nExperience supporting enterprise-scale AI platforms.\nExposure to GenAI, LLMOps, and Agentic AI frameworks.\nThe expected salary range for this position is €56500 - €75300. This role may also be eligible for annual short-term incentive compensation. 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