Machine Learning Engineer

Job Description

Job Title: ML Ops Engineer\n
\nLocation: Downtown Cincinnati\n
\nIndustry: Banking & Financial Services\n
\nYears of Experience: 3+ years\n
\n
\nTOP SKILLS:\n
\nAWS Sagemaker\n
\nPython\n
\nSQL\n
\nMLOps\n
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\nWhat You’ll Do\n
\nJoin our Data Science Enablement squad as a Senior Machine Learning Engineer. You will\n
\nuse an existing batch inference model to establish a secure, automated deployment pipeline.\n
\nThis role involves both engineering and change management, including architecture and\n
\ntraining, with a focus on educating data scientists and other Data Science Enablement\n
\nmembers on MLOps. Once the foundational deployment framework is in place, you will\n
\nenable additional MLOps capabilities such as MLFlow, A/B testing, real-time endpoints, and\n
\nfurther automation with Model Risk Management (MRM).\n
\n
\nKey Responsibilities:\n
\n• Develop and implement a secure, automated deployment pipeline.\n
\n• Educate and mentor team members on MLOps practices.\n
\n• Balance engineering tasks with change management and training.\n
\n• Enhance MLOps capabilities with advanced tools and techniques.\n
\n
\nPreferred Experience:\n
\n• Experience in highly regulated industries like banking, finance, or healthcare.\n
\nQualifications:\n
\n
\nExperience:\n
\n• Minimum of 3-5+ years of experience in machine learning and MLOps.\n
\n• Proven experience with AWS Sagemaker and building end-to-end machine\n
\nlearning models.\n
\n• Experience with data integration and management using IBM DB2 and Snowflake\n
\n(or like databases)\n
\n• Strong understanding of CI/CD pipelines and automation tools.\n
\nTechnical Skills:\n
\n• Proficiency in programming languages such as Python, R, SQL and/or Java.\n
\n• Use of Fifth Third standard DevOps tools such as Jira, Terraform, GitHub, Jenkins\n
\n• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).