ML Engineer - MLOps (W2 Candidates only)

Need Applied ML Engineer to design, deploy, and operationalize machine-learning models that power the Decision Engine, enabling intelligent selection of the most relevant decision using real-time and historical data.This role focuses on building and integrating Python-based ML models (e.g., propensity, ranking, uplift, or optimization models), serving models via low-latency APIs, and integrating with feature stores, streaming pipelines (Kafka or equivalent), and decisioning services built in Nod

ML / Applied AI Engineer (MLOps / Applied ML Platform Engineering Targeted SME Support) Required Qualifications 6+ years of experience in Applied ML Engineering, MLOps, or ML Platform EngineeringStrong understanding of ML model lifecycle management (data training deployment monitoring)Experience designing training and feature pipeline architecturesProven ability to build production-grade systems for:model packaging and deploymentversioning and artifact managementevaluation and monitoringExperien

Principal MLOps Engineer Remote role (Need someone based in Mexico) Job Summary We are seeking a highly experienced Principal MLOps Engineer with 5 10 years of industry experience to lead the design, deployment, and optimization of machine learning infrastructure. This role requires deep expertise in Kubernetes (K8s), cloud-native technologies, and scalable ML systems. The ideal candidate will drive best practices in MLOps and collaborate with cross-functional teams to deliver robust AI solution