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 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
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- 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. xysqume
- Project Focus: AI, Computer Vision, Sensor Integration, Edge AI, and Innovation-Led Product Development.
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