Machine Learning Engineer

Title: Machine Learning Engineer IV Considering applying for this job Do not delay, scroll down and make your application as soon as possible to avoid missing out. Location: 38 Fountain Square Plaza, Cincinnati, OH 45202 Duration: 12 Months contract Must Have: Amazon SageMaker, CI/CD, Dev Op tools like Jira, Terraform, GitHub, Docker, Experience in a highly regulated industry such as Banking/Financial/Healthcare, Python, SQL, Terraform Nice To Have: DBT, Java, Snowflake JOB DESCRIPTION Join our Data Science Enablement squad as a Senior Machine Learning Engineer. You will use an existing batch inference model to establish a secure, automated deployment pipeline. This role involves both engineering and change management, including architecture and training, with a focus on educating data scientists and other Data Science Enablement members on MLOps. Once the foundational deployment framework is in place, you will enable additional MLOps capabilities such as MLFlow, A/B testing, real-time endpoints, and further 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: 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. Technical Skills: Proficiency in programming languages such as Python, R, SQL and/or Java. Use of Fifth Third standard DevOps tools such as Jira, Terraform, GitHub, Jenkins Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).