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At Quercus, we develop robust, computer-vision-based systems that operate in real production environments. We are looking for a Computer Vision / Machine Learning Engineer to join our R&D team and work closely with a small group of machine learning and computer vision engineers focused on continuously improving our core technologies. In this role, you will actively contribute to the implementation, optimization, and continuous improvement of deep learning models used in our products. Your work will focus primarily on license plate recognition, vehicle detection, and parking occupancy, helping to improve accuracy, robustness, and performance under real-world conditions.
Job Responsibility:
Be part of a small, agile, and product-oriented R&D team focused on computer vision solutions deployed in production
Continuously improve existing computer vision and deep learning models through experimentation, evaluation, and iteration
Analyze model performance using real-world data, identify failure cases and propose improvements
Implement, train, and optimize machine learning and computer vision models, mainly using Python-based workflows
Contribute to the integration of models into production pipelines
Monitor and operate machine learning models in production environments
Share insights and technical findings with the rest of the computer vision team
Requirements:
Engineering degree (preferably in Computer Science) or equivalent practical experience in computer vision or machine learning
Strong experience developing software in Python for machine learning and computer vision workflows
Solid understanding of software engineering fundamentals
Practical experience working with machine learning models
Experience developing and running applications in Linux environments
Ability to work with existing code-bases and contribute to production-ready systems
Good communication and collaboration skills
Fluent Catalan and/or Spanish, with English at B2 level or higher
Nice to have:
Experience with computer vision libraries such as OpenCV
Experience with deep learning frameworks (PyTorch, TensorFlow, Keras)
Familiarity with model deployment and inference pipelines
C++ knowledge and experience integrating ML models into production systems
Experience with parallel or high-performance computing
Familiarity with Git, Docker and VSCode
Experience handling real-world datasets
What we offer:
Flexible working hours, including short Fridays
Partial remote work
Access to training and professional development programs
A salary package aligned with experience, including additional benefits