Design and prototype deep learning models for wireless signal processing tasks such as channel estimation, beam alignment, link adaptation, and scheduling
Work with simulation tools and real-world datasets to build models that generalize across diverse wireless scenarios
Implement, train, and validate neural networks (e.g., CNNs, Transformers, GNNs) using PyTorch or TensorFlow
Collaborate with researchers and system engineers to integrate models into full-stack RAN
Optimize model performance for real-time inference and hardware acceleration
Contribute to model evaluation, benchmarking, and deployment readiness on GPU platforms.
Requirements
MS or PhD in Electrical Engineering, Computer Engineering, or related field (or equivalent experience)
12+ years of experience in wireless communications, signal processing, or AI/ML
Deep understanding of communication systems (e.g., MIMO, OFDM, fading channels) and DSP fundamentals
Strong experience in training and deploying deep learning models for time-series or signal-based tasks
Proficiency in Python and experience with DL frameworks like PyTorch or TensorFlow
Familiarity with tools such as MATLAB, GNU Radio, or NVIDIA Sionna for wireless simulation.
Benefits
Flexible work arrangements
Job title
Senior Deep Learning Engineer – AI for Wireless Systems
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