AI/ML Signal Processing Research Engineer

Applied AI research with a focus on real-time signal processing, decision logic, and anomaly detection. Expertise in modular signal & system architecture, complementing classical ML stacks. Developed SDKs for Audio and Finance. Utilizes physically informed analogy modules and hand-crafted, explainable features & operators. Adheres to reproducible research principles with clear pipelines and deterministic exports. Proficient in Mainstream Deep Learning (TensorFlow) for ML, Deep Learning, and neural networks, focusing on classification, regression, and prediction. Experienced with computation graphs, tensors, gradient descent, GPU-first workflows, tf.keras, and deployment stacks. Employs Big Data strategies and automatic feature learning, while also addressing explainability challenges in Deep Learning.