Job Summary: Develop and optimize computer vision algorithms and machine learning models for agricultural applications, integrating embedded systems and managing datasets. Key Highlights: 1. Development of computer vision and AI algorithms 2. Focus on Machine Learning and Deep Learning with Computer Vision 3. Embedded systems integration and model optimization **Mandatory Requirements:** * Bachelor's degree 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 systems 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:** * Currently pursuing or recently completed Master's degree; * Knowledge of agricultural machinery and farming operations; * Experience in building, maintaining, and ensuring dataset quality; * Experience with model evaluation and best practices for validation. **Responsibilities:** * Develop computer vision algorithms for detection and classification of crops, weeds, and pests, including autonomous navigation and orthomosaic post-processing; * Specify sensors and video processing units, performing dataset preprocessing and analysis; * Implement machine learning models for image classification and segmentation, applying sound data management practices; * 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 (PcD).**
João Silva
Indeed · HR
João Silva
Indeed · HR
