{"schemaVersion":"jobsearcher.job.v1","id":"a07813a535fca8277d997342","url":"https://jobsearcher.com/jobs/a07813a535fca8277d997342","canonicalUrl":"https://jobsearcher.com/jobs/a07813a535fca8277d997342","title":"Machine Learning Engineer","description":"AI/ML Engineer Position Summary:Our partner is a global manufacturer of conveyorized car wash equipment, supporting a complex operation across sales, inventory, production, finance, customer information, work orders, deliveries, and field operations.The organization is transforming how it uses data by building a trusted enterprise platform that supports forecasting, automation, and practical AI-driven decision-making. They are hiring an AI/ML Engineer to turn governed business data into production machine learning solutions that help teams anticipate demand, optimize inventory, improve planning, and make better operational decisions.This role begins where traditional data engineering ends. You’ll design, deploy, monitor, and continuously improve forecasting and predictive models within a modern Databricks environment while owning the full production lifecycle from feature engineering through model performance and retraining.This is an ideal opportunity for an engineer who combines machine learning expertise with strong software engineering practices, production ownership, and a clear understanding of how predictive solutions create measurable business value.Experience and Education:BS in Computer Science, Information Technology, Data Science, or equivalent experience/fieldProven background building, deploying, and supporting machine learning models used in production business environmentsProven ownership of forecasting or predictive analytics models from feature engineering through deployment, monitoring, retraining, and continuous improvementStrong experience using Databricks, Apache Spark, Python, SQL, and MLflow within enterprise environmentsExperience building production feature pipelines and supporting modern data engineering practicesExposure to manufacturing, supply chain, logistics, retail, consumer products, or other operationally complex industries preferredExperience integrating machine learning solutions with enterprise data platforms, ERP systems, or business applicationsSkills and Strengths:Production Machine LearningTime Series ForecastingDatabricksPythonPredictive AnalyticsModel ServingModel MonitoringFeature EngineeringApache SparkSQLMLFlowModel Performance EvaluationModel Drift DetectionModel RetrainingData PipelinesPredictive ModelingData GovernanceLakehouseDelta LakeUnity CatalogPrimary Job Responsibilities:Design, build, deploy, and support production machine learning solutions that drive meaningful business decisionsOwn the complete machine learning lifecycle, including feature engineering, training, deployment, monitoring, retraining, and continuous improvementDevelop forecasting models supporting demand planning, inventory optimization, financial planning, operations, and productionBuild and maintain production feature pipelines and datasets within DatabricksMonitor prediction accuracy, model drift, operational performance, and overall model healthInvestigate production model issues and improve solutions as business conditions and data evolvePartner with business stakeholders to understand operational challenges before designing technical solutionsTranslate manufacturing, supply chain, commercial, and operational data into scalable predictive solutionsCollaborate with data engineering teams to integrate trusted enterprise data into production machine learning workflowsEstablish best practices for model lifecycle management, testing, governance, documentation, and production supportEnsure forecasting and machine learning solutions are built on trusted, governed enterprise dataContribute to the organization's long-term AI, automation, and intelligent application strategyApply modern AI tools to improve engineering productivity while maintaining sound software engineering practicesCommunicate technical decisions, model assumptions, and business impact to both technical and non-technical stakeholders","company":"Ranger Technical Resources","rawCompany":"ranger technical resources","city":"Lauderhill","state":"FL","isRemote":false,"isActive":false,"createdAt":"2026-08-12T10:53:20.048Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"AI/ML Engineer Position Summary:Our partner is a global manufacturer of conveyorized car wash equipment, supporting a complex operation across sales, inventory, production, finance, customer information, work orders, deliveries, and field operations.The organization is transforming how it uses data by building a trusted enterprise platform that supports forecasting, automation, and practical AI-driven decision-making. They are hiring an AI/ML Engineer to turn governed business data into production machine learning solutions that help teams anticipate demand, optimize inventory, improve planning, and make better operational decisions.This role begins where traditional data engineering ends. You’ll design, deploy, monitor, and continuously improve forecasting and predictive models within a modern Databricks environment while owning the full production lifecycle from feature engineering through model performance and retraining.This is an ideal opportunity for an engineer who combines machine learning expertise with strong software engineering practices, production ownership, and a clear understanding of how predictive solutions create measurable business value.Experience and Education:BS in Computer Science, Information Technology, Data Science, or equivalent experience/fieldProven background building, deploying, and supporting machine learning models used in production business environmentsProven ownership of forecasting or predictive analytics models from feature engineering through deployment, monitoring, retraining, and continuous improvementStrong experience using Databricks, Apache Spark, Python, SQL, and MLflow within enterprise environmentsExperience building production feature pipelines and supporting modern data engineering practicesExposure to manufacturing, supply chain, logistics, retail, consumer products, or other operationally complex industries preferredExperience integrating machine learning solutions with enterprise data platforms, ERP systems, or business applicationsSkills and Strengths:Production Machine LearningTime Series ForecastingDatabricksPythonPredictive AnalyticsModel ServingModel MonitoringFeature EngineeringApache SparkSQLMLFlowModel Performance EvaluationModel Drift DetectionModel RetrainingData PipelinesPredictive ModelingData GovernanceLakehouseDelta LakeUnity CatalogPrimary Job Responsibilities:Design, build, deploy, and support production machine learning solutions that drive meaningful business decisionsOwn the complete machine learning lifecycle, including feature engineering, training, deployment, monitoring, retraining, and continuous improvementDevelop forecasting models supporting demand planning, inventory optimization, financial planning, operations, and productionBuild and maintain production feature pipelines and datasets within DatabricksMonitor prediction accuracy, model drift, operational performance, and overall model healthInvestigate production model issues and improve solutions as business conditions and data evolvePartner with business stakeholders to understand operational challenges before designing technical solutionsTranslate manufacturing, supply chain, commercial, and operational data into scalable predictive solutionsCollaborate with data engineering teams to integrate trusted enterprise data into production machine learning workflowsEstablish best practices for model lifecycle management, testing, governance, documentation, and production supportEnsure forecasting and machine learning solutions are built on trusted, governed enterprise dataContribute to the organization's long-term AI, automation, and intelligent application strategyApply modern AI tools to improve engineering productivity while maintaining sound software engineering practicesCommunicate technical decisions, model assumptions, and business impact to both technical and non-technical stakeholders","datePosted":"2026-08-12T10:53:20.048Z","dateModified":"2026-08-12T10:53:20.048Z","hiringOrganization":{"@type":"Organization","name":"Ranger Technical Resources","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Lauderhill","addressRegion":"FL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"a07813a535fca8277d997342"},"url":"https://jobsearcher.com/jobs/a07813a535fca8277d997342"}}