• Design, train, and evaluate models for tasks ranging from object detection and classification to anomaly detection and sensor-based inference • Optimize model architectures and inference pipelines for performance on embedded/edge hardware under compute and bandwidth constraints • Contribute to dataset development and labeling strategy, including data augmentation, synthetic data generation, and domain adaptation • Support prototyping and experimentation across a variety of AI subfields, including computer vision, signal processing, and multi-modal fusion • Implement real-time pipelines for processing sensor data on-device and in cloud environments • Develop tools and scripts for benchmarking, data visualization, and debugging ML model performance • Stay current with the latest research and tools in machine learning and evaluate their applicability to our product roadmap • Participate in code reviews, team knowledge sharing, and internal technical documentation