We are seeking a Computer Vision & ML Engineer to develop a real‑time productivity monitoring system for textile production lines. The role involves fine‑tuning video‑based models, designing training pipelines, and collaborating with engineering teams to integrate solutions into production. Candidates should have 2+ years of experience in deep learning, proficiency in PyTorch, and knowledge of video architectures such as FACT, SlowFast, or 3D CNNs. The position is a CDI in Casablanca with a hybrid working model.

We are looking for an experienced ML Technical Lead to spearhead the development of a next‑generation shelf‑recognition system at z.systems. The role involves leading a small team, designing training pipelines for YOLOv8, managing synthetic data workflows, and ensuring robust deployment across our retail network. Candidates should have deep expertise in computer vision, PyTorch, and distributed training on AWS, along with strong leadership and communication skills.

Computer Vision / Machine Learning Engineer – Model Training at Haldorix in Casablanca. Join a dynamic startup studio focused on turning operational challenges into scalable tech solutions. In this role you’ll design, fine‑tune, and deploy video‑based models for industrial vision, working on real‑time productivity monitoring for textile production lines. You’ll collaborate with a small, high‑performing engineering team, leveraging PyTorch, FACT, SlowFast, and 3D CNNs, and applying data augmentation, GPU optimisation, mixed precision, and MLOps practices. The position offers a hybrid work model, competitive salary, and the chance to shape cutting‑edge AI products in a fast‑paced environment.

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.