Kforce has a client that is seeking a Senior Machine Learning Ops Engineer in Cincinnati, OH. Summary: We are seeking a highly skilled MLOps Engineer to build, scale, and support our Google Vertex machine learning platform to enable a multi-model serving environment. This role is central to building reusable infrastructure components (i.e., infra as code), model deployment pipelines, and provide a collection of templates that accelerate model deployment, monitoring, and support for domain teams. Responsibilities: * Collaborate closely with data scientists, other MLOps engineers, and product teams to ensure that models are deployed efficiently that are observable, maintainable, and aligned with business goals * This work will empower domain teams to independently run, support, and monitor their models using platform-provided tools and best practices * Design and implement reusable modules and templates for model training, deployment, and monitoring across Vertex AI and other cloud platforms * Build and maintain scalable CI/CD pipelines for ML workflows, enabling rapid iteration and safe promotion across environments * Develop tooling and automation to support overall platform observability, including drift detection, performance tracking, request latency, and alerting * Partner with domain teams to onboard models into the platform, ensuring alignment with operational standards and SLAs * Maintain and evolve the feature store, model registry, and endpoint management systems to support high-throughput, low-latency inference * Collaborate with leadership to define and enforce governance policies, including versioning, rollback strategies, and access controls * Provide technical guidance and support to domain teams, enabling self-service capabilities and reducing operational bottlenecks * Work closely with data scientists to understand their needs and efficiently integrate their models into production systems