Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact. We’re looking for a Computer Vision / Machine Learning Engineer - Model training to join our team. You’ll develop a real-time productivity monitoring system for textile production lines from model fine-tuning to deployment.

As a Machine Learning Engineer – Video Model Training, you will be responsible for designing, fine-tuning, and deploying video-based models for industrial vision. Your key responsibilities include: - Research & Discovery - Analyze existing datasets and identify optimal data sampling and labeling strategies. - Evaluate prior model performance and determine improvement paths through Active Learning. - Design & Definition - Set up and structure video training pipelines for short clips. - Design and test data augmentation workflows for robustness. - Execution & Collaboration - Fine-tune the FACT-tiny architecture on domain-specific data. - Implement and monitor GPU-optimized training using mixed precision and TensorBoard. - Manage model checkpoints and retraining cycles during Active Learning. - Feedback & Iteration - Conduct iterative experiments to maximize accuracy and inference efficiency. - Work closely with the engineering team to integrate the model into the production system. - Innovation & Learning - Explore alternative architectures such as SlowFast or 3D CNNs for performance comparison. - Document key findings and best practices for future model deployments.

You’ll join a small, high-performing engineering team working at the intersection of computer vision, data, and industrial operations. The team combines expertise from AI research, software engineering, and product integration, and operates in short, focused sprints. You’ll report directly to the **Lead computer vision engineer**, collaborating daily with backend and computer vision engineers to deliver an end-to-end operational solution.

Required - 2+ years of experience in Deep Learning model training and optimization. - Strong proficiency with PyTorch. - Experience with video architectures such as FACT, SlowFast, or 3D CNNs. - Solid understanding of data augmentation tools (Albumentations, imgaug). - Familiarity with GPU optimization, mixed precision, and training monitoring (TensorBoard). - Proven ability to iterate quickly and improve model performance under time constraints. Nice to Have - Experience in industrial vision or manufacturing contexts. - Exposure to MLOps workflows (versioning, checkpoints, pipeline reproducibility). - Familiarity with Active Learning loops in computer vision. - Hands-on experience with real-time inference pipelines or edge deployments.

- Opportunity to work on a cutting-edge applied AI project with real industrial impact. - Close collaboration with an expert technical team and startup founders. - Freedom to experiment, learn, and push the boundaries of real-time vision systems.