Computer Vision Engineer – Agritech team

Oròbix is looking for a talented Computer Vision Engineer who thrives on working in the field, enjoys hands-on problem-solving, and is excited about bringing AI solutions to real-world zootechnical environments. This role requires availability for travel and a strong inclination for practical implementation.

As a Computer Vision Engineer, you will be at the forefront of developing cutting-edge AI solutions for the agricultural and zootechnical sectors. This role involves both research and hands-on implementation of deep learning models, with a focus on image analysis. You will actively work on-site, engaging directly with end-users and customers to ensure seamless deployment and adoption of AI-driven solutions.

Key responsibilities

• Design, develop, and deploy computer vision models for real-world animal welfare and zootechnical applications.

• Participate in fieldwork, testing AI solutions directly in production environments.

• Implement algorithms into production-ready solutions and ensure their usability for customers.

• Oversee the full AI lifecycle, from initial research and development to deployment and ongoing monitoring.

• Collaborate closely with project managers, technicians, software developers, and end-users.

• Continuously explore and integrate new techniques to improve AI-driven vision solutions.

Required Skills & Qualifications

• Good software development skills and experience in languages such as Python or C++;
• Background in image processing or computer vision
• Familiarity with deep learning frameworks, such as PyTorch, Keras, TensorFlow, etc
• Practical experience contributing to a code base with code versioning systems such as Git.
• Strong problem-solving skills and the ability to translate AI research into practical applications.
• Fluency in English
• Fluency in Italian
• Willingness to travel and work directly in zootechnical settings.
• At least 1 or 2 years of relevant work experience.
• M. Sc. in Computer Science or similar.

Preferred qualifications (Nice to Have)

• Prior experience deploying computer vision models in agriculture or zootechnical fields.
• Interest in animal welfare, precision farming, and livestock monitoring.