Research and Development Engineer (Computer Vision)

Description

Job Summary: Develop computer vision algorithms and implement machine learning models for image classification and segmentation, optimizing them for embedded hardware. Key Highlights: 1. Focus on Artificial Intelligence, Machine Learning, and Deep Learning 2. Development of computer vision algorithms 3. Optimization of models for embedded hardware **Mandatory Requirements:** * Bachelor's degree completed in Computer Engineering; Control and Automation Engineering; Electrical Engineering; or related engineering fields; * Advanced knowledge of Artificial Intelligence: Machine Learning and Deep Learning, with focus on Computer Vision; * Advanced proficiency in Python and AI libraries (OpenCV, PyTorch and/or TensorFlow); * Intermediate knowledge of C\+\+ for embedded system integration; * Knowledge of robotics libraries such as ROS / ROS2; * Knowledge of containerization and system integration (Docker); * Practical knowledge of software version control using GIT; * Experience with cloud computing platforms (AWS, Azure, or GCP); * Intermediate English (technical reading and writing); * Willingness to travel; **Desirable Requirements:** * Pursuing or having completed a Master's degree (final year or graduated); * Knowledge of agricultural machinery and agricultural operations; * Experience in building, maintaining, and ensuring dataset quality; * Experience with model evaluation and best practices in validation. **Responsibilities:** * Develop computer vision algorithms for detection and classification of crops, weeds, and pests, including autonomous navigation and post-processing of orthomosaics; * Define sensors and video processing units, performing pre-processing and dataset analysis; * Implement machine learning models for image classification and segmentation, applying best practices in data management; * Conduct neural network testing and validation, evaluating metrics and technical requirements; * Optimize models for execution on embedded hardware and support integration with demanding systems; * Participate in creating training pipelines, dataset selection, and annotation processes for robust and generalizable models. **This position is also open to persons with disabilities (PwD).**