AI/MLOps Engineer

Key Responsibilities Design, build, and manage end-to-end ML pipelinesDeploy and maintain machine learning models in productionImplement CI/CD pipelines for ML workflowsAutomate model training, versioning, and deployment processesMonitor model performance, data drift, and system healthManage containerized deployments using Docker and KubernetesCollaborate with cross-functional teams to improve ML deliveryEnsure best practices in scalability, security, and reliability Required Skills & Qualifica

About the Opportunity Driscoll's is building an AI-assisted R&D capability that depends on trusted data, governed delivery patterns, secure environments, and production-grade model operations. This role sits within an emerging R&D IT function embedded in Global R&D and partners closely with Global IS, scientists, product leads, and engineers to define how AI is safely and repeatedly deployed across breeding, genomics, lab, phenotyping, sensory, and agronomy workflows. We are seeking an AI / MLO

If you're ready to be part of our legacy of hope and innovation, we encourage you to take the first step and explore our current job openings. Your best is waiting to be discovered. Day - 08 Hour (United States of America) We are seeking a high-caliber Senior AI Platform & ML Ops Engineer to architect the "layered" infrastructure required for autonomous, agentic systems within Stanford Healthcare. In this role, you will be the "Master Chef" of our AI ecosystem, seamlessly folding Expert-Level D

An industry-leading technology and analytics organization is hiring an AI/ML Operations Engineer to support its rapidly growing artificial intelligence initiatives. This full-time opportunity offers the chance to work with modern cloud technologies, machine learning platforms, containerized environments, and production AI systems. The ideal candidate will have experience deploying machine learning solutions, building cloud infrastructure, and supporting MLOps best practices across enterprise env