AI Computer Vision Developer

Airobotics is seeking an AI Data Scientist with a strong focus on computer vision applications to join their team. The role involves designing, training, and optimizing AI vision models for object detection, tracking, and SLAM, as well as deploying them on edge devices like NVIDIA Jetson and Raspberry Pi. The candidate will also work on non-vision AI tasks and collaborate with cross-disciplinary engineers to integrate models into production systems.

Responsibilities

• Computer Vision & AI Model Development
• Design, train, and optimize AI vision models for object detection, recognition, tracking, and SLAM.
• Develop robust pipelines for real-time video and image analysis.
• Deploy and optimize models for edge environments (Jetson, Raspberry Pi, etc.) as well as cloud systems.
• Stay updated with state-of-the-art methods in computer vision, deep learning, and robotics-related AI.
• Experiment with novel techniques to improve the accuracy, efficiency, and robustness of vision models.
• Occasionally design and implement AI models for non-vision data (e.g., sensor data, tabular data, time-series, NLP-based tasks).
• Integrate multimodal AI approaches combining vision and non-vision data for enhanced decision-making.
• Collect, curate, and annotate datasets for AI model training and validation.
• Implement data augmentation, preprocessing, and synthetic data generation pipelines.
• Define and monitor key performance metrics for deployed AI systems.
• Work closely with engineers from different disciplines to integrate AI models into production systems.
• Document models, pipelines, and findings for reproducibility and knowledge sharing.

Requirements

• Strong background in deep learning frameworks (e.g., PyTorch, TensorFlow).
• Proven hands-on experience with object detection and tracking models (e.g., YOLO-based frameworks).
• Experience in SLAM and real-time computer vision applications.
• Expertise in building end-to-end AI pipelines, including preprocessing, training, validation, and deployment.
• Experience with real-time inference on edge and GPU platforms.
• Solid understanding of machine learning concepts, probability, and optimization.
• Proficiency in Python and scientific computing libraries (e.g., NumPy, OpenCV, SciPy, scikit-learn).
• Experience in training, fine-tuning, quantizing, and deploying models on edge devices (e.g., Jetson, Raspberry Pi, etc.) and GPUs.

Nice to have

• Knowledge of 3D vision techniques (stereo vision, depth sensing, LiDAR fusion).
• Exposure to non-vision AI applications such as NLP or time-series forecasting.
• Strong problem-solving skills and ability to work in fast-paced R&D environments.

Benefits

• Opportunity to work on cutting-edge AI vision and robotics challenges.
• Collaborative and innovative work environment.
• Professional growth in a cross-disciplinary AI and robotics setting.