Tasks Design, develop, train, and optimise machine learning models for real-world business challenges. Build and maintain scalable ML pipelines covering data preparation, model training, validation, deployment, and monitoring. Implement and enhance MLOps practices including CI/CD automation, model versioning, experiment tracking, and model governance. Deploy and manage ML workloads on cloud platforms such as AWS, Azure, or GCP. Utilise Docker, Kubernetes, MLflow, and other modern MLOps technologies to support production-scale AI solutions. Monitor model performance, drift detection, latency, and infrastructure utilisation to ensure reliability and scalability. Collaborate with Data Scientists, Software Engineers, Data Engineers, and business stakeholders to operationalise AI solutions. Requirements 9+ Years Strong Python programming experience Hands-on expertise with Scikit-Learn, TensorFlow, PyTorch Strong understanding of MLOps, ML lifecycle management, Model deployment Experience with MLflow / Kubeflow, CI/CD pipelines, Docker, Kubernetes, Git Cloud experience with at least one: AWS, Azure, Google Cloud Platform (GCP) Experience with REST APIs, model serving, monitoring, logging, and production support Excellent analytical, communication, and problem-solving skills Schedule Onsite Only (No Remote) Pay $110K+ How to apply Include Visa Status and Current Location with your application. Location Columbus, OH (Onsite)