{"id":2212575,"url":"https://alion.io/job/madiff-mlops-engineer-portfolio-optimisation-and-customer-analytics-platform-banking","title":"MLOps Engineer – Portfolio Optimisation and Customer Analytics Platform (Banking)","company":{"id":4374669,"name":"Madiff","domain":"madiff.eu","url":"https://alion.io/company/madiff-2","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"unspecified","remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"MLFlow","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-10T03:53:37Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-14T12:45:23Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"This is a remote position.\nWe are looking for an MLOps Engineer to support an enterprise analytics and optimisation platform within an international banking environment. The platform underpins pricing, capital allocation, and customer lifetime value decisions across multiple markets and product lines. It operates at scale with regular model retraining cycles and governed analytics processes. Analytical outputs feed both traditional reporting layers and LangChain and LangGraph based GenAI workflows that generate automated insights and scenario analysis. This role focuses on operationalising analytical models and ensuring stable, repeatable production workflows.\n\nResponsibilities\nDesign and operate training and deployment pipelines for analytical and optimisation models\nAutomate model retraining, validation, and promotion processes\nEnsure reproducibility and consistency across development, testing, and production environments\nSupport scalable analytical workloads across cloud platforms\nEnable structured exposure of model outputs to LangChain and LangGraph workflows\nMonitor performance, stability, and reliability of ML pipelines\nCollaborate closely with data scientists and analytics teams to streamline experimentation to production\nRequirements\nStrong experience in MLOps or ML platform engineering\nSolid Python skills for automation and tooling\nHands on experience with Docker and Kubernetes\nPractical experience with MLflow or similar model lifecycle management tools\nExperience with workflow orchestration tools such as Airflow\nHands on experience with CI/CD pipelines\nExperience working with cloud data platforms\nStrong understanding of reproducibility and environment management\nFluent English for professional collaborationNice to have\n\nExperience integrating ML outputs with LangChain or LangGraph workflows\nExposure to banking, finance, or regulated environments\nExperience with optimisation models or large scale analytical platforms\nUnderstanding of data governance and audit requirements\nBenefits\nSolid, competitive salary\nWork in a multinational environment on international projects\nComprehensive healthcare\nLong-term B2B contract with a stable project pipeline\nRemote work 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