Computer Vision Engineer
Pubblicato il 09-09-2026 - Hermes Corporate in Roma
We are looking for a skilled Computer Vision&Robotics; Engineer to design, develop, and deploy advanced vision-based solutions for real-world applications. You will work at the intersection of AI and robotics, building robust systems that operate reliably in production and real-time environments.
Key Responsibilities
- Design, develop, and deploy computer vision models for real-world applications - Build and optimize deep learning models for tasks such as object detection, segmentation, classification, tracking, and pose estimation - Develop scalable image and video processing pipelines for both training and inference - Deploy and optimize models for real-time and edge environments, ensuring low latency and high efficiency - Integrate vision models into production systems, including automated and semi-autonomous platforms - Collaborate with cross-functional teams (software, hardware, product) to deliver end-to-end solutions - Evaluate model performance using real-world data and continuously improve accuracy, robustness, and efficiency - Stay up to date with the latest advancements in computer vision, deep learning, and applied AI
Required Qualifications
- Bachelor’s degree in Computer Science, Artificial Intelligence,
or a related field - 2+ years of hands-on experience in computer vision and deep learning - Strong programming skills in Python - Experience with deep learning frameworks such as PyTorch or TensorFlow - Solid understanding of core computer vision concepts (image processing, CNNs, feature extraction, object detection) - Experience training and deploying machine learning models in production environments - Familiarity with model optimization techniques (e.g., quantization, pruning, ONNX) - Experience working with image/video datasets and data pipelines - Strong analytical and problem-solving skills
Preferred Qualifications
- Master’s degree in Computer Vision, Machine Learning, or a related field - Experience with real-world or industrial AI applications - Exposure to robotics or autonomous systems - Familiarity with edge deployment or performance-constrained environments - Experience with cloud-based ML infrastructure and MLOps workflows
Nice to Have
- Experience with infrastructure robustness testing to ensure system stability and reliability - Hands-on experience updating and validating software on physical robotic systems - Exposure to real-world field testing and evaluating system performance in live environments - Familiarity with end-to-end system validation, including testing under varying operating conditions