11 set - Modena
OXI
Job Description – AI & Computer Vision Engineer
Dato l'elevato interesse per questa posizione, la preghiamo di candidarsi tempestivamente se il suo profilo è in linea con il ruolo.
Location: Modena
Key Responsibilities
Position Summary
We are seeking anAI & Computer Vision Engineerto 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.
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Project Focus:AI, Computer Vision, Sensor Integration, Edge AI, and Innovation-Led Product Development.
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