Haldorix, a startup studio based in Casablanca, is transforming operational challenges into scalable business opportunities through technology. We are looking for a Computer Vision/Machine Learning Engineer – Inference & Model Deployment to join our industrial vision venture. Your responsibilities will include:

• Model Optimization & Deployment: Export and optimize deep learning models using ONNX and TensorRT (INT8, FP16) for efficient inference on GPU.
• Active Learning Loop: Manage data collection, annotation, and correction pipelines within CVAT to continuously improve model performance.
• Performance Benchmarking: Conduct GPU stress tests and benchmark latency, throughput, and accuracy across deployment environments.
• Validation & QA: Lead field validation sessions, perform detailed QA checks, and ensure robustness in real‑time production conditions.
• Automation & Scalability: Develop scripts and tools to streamline model conversion, quantization, and deployment workflows.
• Collaboration & Documentation: Work closely with computer vision and backend engineers to integrate optimized inference pipelines and document performance metrics.
• Continuous Improvement: Analyze bottlenecks, propose optimizations, and refine the active learning feedback loop for model accuracy.
• Testing Culture: Contribute to building a strong testing and profiling culture around ML models in production.

We expect 3–5 years of experience in ML model deployment and inference optimization, strong expertise with TensorRT, ONNX, GPU performance optimization, and proficiency in Python. Familiarity with CVAT, Docker, Kubernetes, CI/CD, and industrial computer vision is a plus. A Bachelor’s degree (Master level) in Computer Science, Engineering, or a related field is required. The role is a CDI with a hybrid working arrangement in Casablanca.