AI/ Machine Learning Engineer

About Us

Aonic is an end-to-end drone solutions company. We began by providing drone services and has since evolved into a comprehensive solutions provider - creating our own drones, supplying major brands like DJI, and now expanding into distributing smart home products.

With expertise across B2B and B2C segments, we deliver end-to-end solutions through six integrated verticals: agriculture, industrial, services, retail, academy and lifestyle.

At Aonic, our mission is to empower businesses and end users with innovative ecosystems that drive efficient living through smart technology.

About the Role

We’re on the lookout for an AI/ML Engineer who can bring together the power of computer vision, drone imagery, and geospatial intelligence to develop a cutting-edge system for automated tree detection and counting.

Key Responsibilities

• Develop & Train Models – Design, train, and fine-tune deep learning models (e.g., YOLO) to detect and count trees from aerial images.
  
• Build ML Pipelines – Create robust end-to-end pipelines for image preprocessing, data augmentation, training, validation, and evaluation.
  
• Photogrammetry Integration – Stitch raw drone imagery into high-resolution orthomosaics using Agisoft Metashape or similar tools.
• Deploy Seamlessly – Convert and optimize models into ONNX format for smooth integration into our mapping platform, enabling dynamic updates.
  
• Collaborate Across Teams – Work closely with our GIS specialists and software engineers to ensure successful deployment and scalability.
• Innovate for Impact – Contribute to the future of AI-driven forestry, agriculture, and land management through real-time geospatial intelligence.

About You

• Degree in Computer Science, Artificial Intelligence, Geospatial Science, or a related field.
• Minimum 2 years of hands-on experience in building AI/ML solutions for computer vision tasks.
  
• Strong coding skills in Python, with solid grasp of TensorFlow, PyTorch, and OpenCV.
• Practical experience in object detection, segmentation, and working with geospatial data.