Key Responsibilities ● Design and develop object detection & tracking architectures for real-time applications ● Build and maintain image recognition pipelines (data collection, preprocessing, training, deployment) ● Train, evaluate, and optimize neural networks ● Develop tracking algorithms for UAV systems ● Conduct data analysis, model benchmarking, and performance profiling ● Collaborate with hardware and software teams to integrate models into embedded platforms ● Document architecture, research, experiments, and model performance metrics
Required Skills
Machine Learning & Computer Vision ● Experience with TensorFlow (TFLite for edge deployment) ● MobileNet, YOLO, SSD, or similar lightweight architectures ● Model quantization and optimization for resource-constrained devices ● Familiarity with common CV tasks: classification, detection, segmentation, tracking Signal Processing & Applied Math ● Kalman filters (EKF/UKF) and state estimation techniques ● Digital signal processing: FIR/IIR filtering, FFT, convolution ● Knowledge in linear algebra, probability, and statistics Programming & Development ● Python (NumPy, Pandas, OpenCV, scikit-learn) ● C/C++ for performance-critical components ● Unit testing, integration testing, and CI/CD pipelines ● Version control (Git) Embedded Systems ● Deploying ML models on Embedded Linux platforms ● Understanding of hardware constraints and real-time processing requirements
Nice to Have ● Experience with NXP i.MX8M Plus or similar edge AI accelerators ● Background in UAV/drone systems or robotics ● Experience with ONNX, TensorRT, or other inference optimization tools ● Familiarity with ROS or similar middleware frameworks Education ● BSc/MSc in Computer Science, Data Science, Electrical Engineering, Applied Mathematics, or a related field
