{"schemaVersion":"jobsearcher.job.v1","id":"00ecdcfd48804c2dfb7f2a13","url":"https://jobsearcher.com/jobs/00ecdcfd48804c2dfb7f2a13","canonicalUrl":"https://jobsearcher.com/jobs/00ecdcfd48804c2dfb7f2a13","title":"Machine Learning Engineer","description":"Job Title: ML Ops EngineerLocation: Downtown CincinnatiIndustry: Banking & Financial ServicesYears of Experience: 3+ yearsTOP SKILLS:AWS SagemakerPythonSQLMLOpsWhat You'll DoJoin our Data Science Enablement squad as a Senior Machine Learning Engineer. You willuse an existing batch inference model to establish a secure, automated deployment pipeline.This role involves both engineering and change management, including architecture andtraining, with a focus on educating data scientists and other Data Science Enablementmembers on MLOps. Once the foundational deployment framework is in place, you willenable additional MLOps capabilities such as MLFlow, A/B testing, real-time endpoints, andfurther automation with Model Risk Management (MRM).Key Responsibilities:Develop and implement a secure, automated deployment pipeline.Educate and mentor team members on MLOps practices.Balance engineering tasks with change management and training.Enhance MLOps capabilities with advanced tools and techniques.Preferred Experience:• Experience in highly regulated industries like banking, finance, or healthcare.Qualifications:Experience:Minimum of 3-5+ years of experience in machine learning and MLOps.Proven experience with AWS Sagemaker and building end-to-end machine learning models.Experience with data integration and management using IBM DB2 and Snowflake (or like databases)Strong understanding of CI/CD pipelines and automation tools. TechnicalSkills:Proficiency in programming languages such as Python, R, SQL and/or Java.Use of Fifth Third standard DevOps tools such as Jira, Terraform, GitHub, JenkinsKnowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).","company":"LinkedIn","rawCompany":"linkedin","city":"Dayton","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-10-16T05:46:13.609Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Job Title: ML Ops EngineerLocation: Downtown CincinnatiIndustry: Banking & Financial ServicesYears of Experience: 3+ yearsTOP SKILLS:AWS SagemakerPythonSQLMLOpsWhat You'll DoJoin our Data Science Enablement squad as a Senior Machine Learning Engineer. You willuse an existing batch inference model to establish a secure, automated deployment pipeline.This role involves both engineering and change management, including architecture andtraining, with a focus on educating data scientists and other Data Science Enablementmembers on MLOps. Once the foundational deployment framework is in place, you willenable additional MLOps capabilities such as MLFlow, A/B testing, real-time endpoints, andfurther automation with Model Risk Management (MRM).Key Responsibilities:Develop and implement a secure, automated deployment pipeline.Educate and mentor team members on MLOps practices.Balance engineering tasks with change management and training.Enhance MLOps capabilities with advanced tools and techniques.Preferred Experience:• Experience in highly regulated industries like banking, finance, or healthcare.Qualifications:Experience:Minimum of 3-5+ years of experience in machine learning and MLOps.Proven experience with AWS Sagemaker and building end-to-end machine learning models.Experience with data integration and management using IBM DB2 and Snowflake (or like databases)Strong understanding of CI/CD pipelines and automation tools. TechnicalSkills:Proficiency in programming languages such as Python, R, SQL and/or Java.Use of Fifth Third standard DevOps tools such as Jira, Terraform, GitHub, JenkinsKnowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).","datePosted":"2026-10-16T05:46:13.609Z","dateModified":"2026-10-16T05:46:13.609Z","hiringOrganization":{"@type":"Organization","name":"LinkedIn","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dayton","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"00ecdcfd48804c2dfb7f2a13"},"url":"https://jobsearcher.com/jobs/00ecdcfd48804c2dfb7f2a13"}}