MLOps Engineer ID72409

Own the complete lifecycle transition from AI/ML experimentation to reliable, high-performance production deployment; - Build, maintain, and scale the infrastructure, automation, and CI/CD workflows necessary for rapid and efficient model deployment; - Implement robust production monitoring systems, build visibility dashboards, and set up data and concept drift detection to ensure ongoing model accuracy and system reliability; - Manage experiment tracking and model versioning to ensure full reproducibility and traceability of all models in production; - Partner closely with data scientists and AI researchers to translate experimental models into robust, production-ready solutions; - Manage cloud environments and GPU compute resources to ensure systems are not only highly scalable but also cost-effective. We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the infrastructure, pipelines, and automation needed to deploy models efficiently at scale.