We are seeking an experienced MLOps Engineer – Edge AI Specialist to design and deploy on‑premise inference infrastructure for industrial vision systems. The role involves building hybrid edge/cloud architectures, optimizing deep learning models for embedded GPUs, and maintaining CI/CD pipelines for edge deployment. The ideal candidate will have 3–5 years of experience in MLOps, edge computing, and GPU performance profiling, with strong skills in Python, Docker, Kubernetes, and monitoring tools. This position offers the chance to work in a fast‑moving startup studio focused on scalable AI ventures.

We are seeking an experienced MLOps Engineer – Edge AI Specialist to lead the design and deployment of on‑premise inference infrastructure for industrial vision systems. The role involves architecture of hybrid edge/cloud solutions, model optimization for embedded GPUs, CI/CD pipeline development, fleet management, and compliance with GDPR. The ideal candidate has 3‑5 years of production experience, expertise in TensorRT, ONNX, Kubernetes, and Python, and a strong background in real‑time analytics and GPU performance profiling.