AI & Computer Vision Engineer

Job Description – AI & Computer Vision Engineer

Location: Modena

Key Responsibilities

Position Summary

We are seeking an AI & Computer Vision Engineer to drive innovation and proof-of-concept initiatives within advanced machine intelligence applications. The role involves end-to-end ownership of AI solutions, including requirements analysis, data acquisition, model development, deployment, optimisation, and lifecycle management using real-world image and sensor data.

AI & Computer Vision Development

Data Acquisition & Sensor Integration

Field Testing & Validation

Dataset Development & Annotation Management

Model Deployment & Edge AI Optimisation

MLOps & Lifecycle Management

Research & Innovation

Required Skills & Experience

Assignment Details

• Design and develop AI, Machine Learning (ML), Deep Learning (DL), and Computer Vision solutions for real-world applications.
• Develop, train, evaluate, and continuously improve AI models based on field validation results and operational feedback.
• Perform image processing, feature extraction, and exploratory data analysis to assess data quality and identify edge cases.
• Select, configure, and validate camera systems aligned with project requirements.
• Develop data acquisition frameworks and pipelines for capturing image and sensor data.
• Integrate data from multiple sources, including GPS, CAN bus, machine signals, and other onboard sensors.
• Support field testing activities, including installation and validation of camera and sensor systems.
• Collect and analyse real-world operational data to verify solution performance.
• Troubleshoot hardware and software issues encountered during field deployments and understand practical operating conditions.
• Prepare, organise, and validate datasets for AI model training and evaluation.
• Coordinate with data annotation teams to define labelling standards and review annotation quality.
• Ensure dataset integrity, coverage, and readiness for model development.
• Optimise trained AI models for deployment on edge computing platforms.
• Balance accuracy, latency, inference speed, memory footprint, and hardware constraints to achieve production-ready performance.
• Support deployment, monitoring, and maintenance of AI applications in operational environments.
• Contribute to the complete MLOps lifecycle, including:
• Data acquisition and preparation
• Model training and validation
• Deployment and monitoring
• Retraining and continuous improvement
• Production support and maintenance
• Support research activities, technical feasibility studies, and rapid prototyping initiatives.
• Evaluate emerging AI and Computer Vision technologies for future applications.
• Mentor and provide technical guidance to KU Leuven Master’s thesis students.
• Strong knowledge of Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision.
• Experience working with image processing, computer vision algorithms, and sensor-based data systems.
• Familiarity with camera technologies, data collection frameworks, and field validation activities.
• Understanding of edge AI deployment and model optimisation techniques.
• Experience with MLOps practices and AI model lifecycle management.
• Strong analytical, problem-solving, and troubleshooting capabilities.
• Ability to work in multidisciplinary teams and customer-facing environments.
• Project Focus: AI, Computer Vision, Sensor Integration, Edge AI, and Innovation-Led Product Development.