Role & responsibilities

We are seeking a versatile and high-impact Senior MLOps & Full Stack Systems Engineer to bridge the gap between production machine learning infrastructure and user-facing enterprise platforms. In this hybrid engineering role, you will be responsible for designing, building, and operating end-to-end ML delivery pipelines while engineering the full-stack software interfaces (React frontend + Java/Python backend services) required to operationalize, monitor, and interact with production AI/ML models. The ideal candidate possesses a unique blend of core software engineering rigor and machine learning platform operations. You will build automated CI/CD and Continuous Training (CT) pipelines, manage model registries and feature stores, deploy low-latency model inference microservices, and build full-stack interactive dashboards and admin portals using React (TypeScript) and Java (Spring Boot) / Python (FastAPI/Flask). Key Roles & Responsibilities 1. MLOps & Platform Architecture Design, build, and maintain automated ML lifecycle pipelines spanning data ingestion,



preprocessing, model training, validation, packaging, and continuous deployment (CI/CD/CT). Implement and manage Model Registries, Experiment Tracking, and Feature Stores using tools such as MLflow, Kubeflow, Feast, or Weights & Biases. Package, optimize, and deploy ML models into production as containerized microservices (using Triton Inference Server, TorchServe, TF Serving, or FastAPI). Implement real-time model monitoring, drift detection (data drift, concept drift), latency tracking, and automated retraining workflows using tools like Evidently AI, Prometheus, and Grafana. 2. Backend & Systems Engineering (Java / Python) Architect and implement robust, high-throughput microservices using Java (Spring Boot / Micronaut) or Python (FastAPI / Flask / AsyncIO) to serve as orchestration layers between frontend applications and ML inference engines. Design and implement secure RESTful APIs,

📌 MLOps Engineer- python,react,kubernets (Delhi)
🏢 Cloudxtreme
📍 Delhi