Computer Vision Engineer
Pubblicato il 09-09-2026 - Hermes Corporate in Savona
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.
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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 xlwpduy 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