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In this role, your primary focus will be designing, building, and deploying production-grade machine learning models that extract actionable insights from noisy, and multi-modal sensor data. Your key responsibilities will include:
Model Development: Designing, training, and evaluating classical ML and deep learning architectures (e.g., CNNs, RNNs/LSTMs, Transformers) optimized for time-series forecasting, anomaly detection, gesture recognition, or spatial tracking.
Advanced Architecture Design: Building and fine-tuning state-of-the-art Transformer-based models and Large Language Models (LLMs) adapted for sequential data (e.g., Time-Series Transformers, behavioral embeddings, and tokenized sensor streams).
Signal Processing & Feature Engineering: Implementing digital signal processing (DSP) techniques; including filtering, windowing, fast Fourier transforms (FFT). To clean, calibrate raw, noisy sensor data...