We are seeking an MLOps Engineer to join a major company that aggregates broad and deep property data and generates analytics informing smart decision-making and property-level insights relied upon by hundreds of thousands of users in the real estate industry.In this role, you will help transform systems to the cloud, enabling cost optimization, improved availability and reliability through architectural improvements, and enhanced analytics with better TTM. You will focus on streamlining the process of taking machine learning models to production, as well as maintaining and monitoring them.ResponsibilitiesUnderstand and manage the ML systems lifecycleFrame ML problems based on business objectivesDesign data solutions tailored to the problem at handPerform data preparation and processingConduct model training and experimentationBuild and automate ML pipelinesDeploy models to the production systemMonitor, optimize,



and maintain models in productionRequirements2+ years of experience in an MLOps or similar roleProficiency in PythonExpertise in Google Vertex AI and Google Vertex AI PipelinesSkills in monitoring ML models in productionFamiliarity with Jenkins and DockerEnglish proficiency at B1+ level or aboveNice to haveBackground in AI Solution Engineering and Prompt EngineeringKnowledge of Agentic SDKs and Google Agent Development KitExperience with Google Cloud Platform, Ansible, and TerraformFamiliarity with Kubeflow and KubernetesProficiency in Groovy and JetBrains PyCharmWe offerInternational projects with top brandsWork with integral teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qual

📌 MLOps Engineer (Colombia)
🏢 EPAM Systems
📍 Colombia