AI & Computer Vision Engineer

ph3Job Description – AI Computer Vision Engineer /h3 pLocation: Modena /p h3Key Responsibilities /h3 h3Position Summary /h3 pWe are seeking an bAI Computer Vision Engineer /b 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. /p h3AI Computer Vision Development /h3 h3Data Acquisition Sensor Integration /h3 h3Field Testing Validation /h3 h3Dataset Development Annotation Management /h3 h3Model Deployment Edge AI Optimisation /h3 h3MLOps Lifecycle Management /h3 h3Research Innovation /h3 h3Required Skills Experience /h3 h3Assignment Details /h3 ul liDesign and develop AI, Machine Learning (ML), Deep Learning (DL), and Computer Vision solutions for real-world applications. /li liDevelop, train, evaluate, and continuously improve AI models based on field validation results and operational feedback. /li liPerform image processing, feature extraction, and exploratory data analysis to assess data quality and identify edge cases. /li liSelect, configure, and validate camera systems aligned with project requirements. /li liDevelop data acquisition frameworks and pipelines for capturing image and sensor data. /li liIntegrate data from multiple sources, including GPS, CAN bus, machine signals, and other onboard sensors. /li liSupport field testing activities, including installation and validation of camera and sensor systems. /li liCollect and analyse real-world operational data to verify solution performance. /li liTroubleshoot hardware and software issues encountered during field deployments and understand practical operating conditions. /li liPrepare, organise, and validate datasets for AI model training and evaluation. /li liCoordinate with data annotation teams to define labelling standards and review annotation quality. /li liEnsure dataset integrity, coverage, and readiness for model development. /li liOptimise trained AI models for deployment on edge computing platforms. /li liBalance accuracy, latency, inference speed, memory footprint, and hardware constraints to achieve production-ready performance. /li liSupport deployment, monitoring, and maintenance of AI applications in operational environments. /li liContribute to the complete MLOps lifecycle, including: /li liData acquisition and preparation /li liModel training and validation /li liDeployment and monitoring /li liRetraining and continuous improvement /li liProduction support and maintenance /li liSupport research activities, technical feasibility studies, and rapid prototyping initiatives. /li liEvaluate emerging AI and Computer Vision technologies for future applications. /li liMentor and provide technical guidance to KU Leuven Master’s thesis students. /li liStrong knowledge of Artificial Intelligence, Machine Learning, Deep Learning, and Computer Vision. /li liExperience working with image processing, computer vision algorithms, and sensor-based data systems. /li liFamiliarity with camera technologies, data collection frameworks, and field validation activities. /li liUnderstanding of edge AI deployment and model optimisation techniques. /li liExperience with MLOps practices and AI model lifecycle management. /li liStrong analytical, problem-solving, and troubleshooting capabilities. /li liAbility to work in multidisciplinary teams and customer-facing environments. /li libProject Focus: /b AI, Computer Vision, Sensor Integration, Edge AI, and Innovation-Led Product Development. /li /ul /p #J-18808-Ljbffr