Senior Wireless Machine Learning Engineer, AI-RAN

About the role

DeepSig is defining the future of wireless communications by merging deep learning with the Radio Access Network (RAN). We are seeking an experienced Technical Lead to architect and drive the development of our next-generation AI-native RAN.

Responsibilities

• Design and train modern deep learning models (Transformers, Vision architectures, etc.) to solve complex physical layer problems, including channel estimation, MIMO detection, and beam management
• Build high-fidelity link-level simulations using NVIDIA Sionna and ray-tracing to train, test, and benchmark AI models against legacy 5G baselines
• Prototype and deploy research models into deployable "dApps" for the Distributed Unit (DU), optimizing inference for latency and compute efficiency on NVIDIA GPUs
• Explore emerging AI-RAN frontiers such as Integrated Sensing and Communications (ISAC), neural scheduling, and channel digital twins
• Drive technical innovation by authoring invention disclosures, filing patents, and generating technical reports to support our standardization team in 3GPP and O-RAN Alliance contributions
• Architect data pipelines for generating synthetic training datasets and developing "Sim-to-Real" transfer techniques to ensure robust performance in real-world networks

Requirements

• Ph.D. or Master’s in Computer Science, Electrical Engineering, or Applied Mathematics with a focus on Deep Learning and/or Communications Systems
• 3+ years of experience designing and training deep neural networks from scratch. Strong grasp of modern architectures and optimization techniques
• Experience applying machine learning to real-time time-series data, signal processing, or physics-based problems (Audio, RF, or similar domains)
• Proven ability to read academic papers and implement their methods in robust Python code
• Experience with differentiable simulation or digital twins (e.g., Sionna, JAX-based physics sims)

Preferred Qualifications

• Understanding of wireless fundamentals (OFDM, MIMO, IQ data) is highly helpful, though we prioritize strong ML intuition over pure communication theory
• Experience with model quantization (FP16/INT8), pruning, or using TensorRT for real-time inference
• Experience writing technical whitepapers or supporting patent filings in a research environment
• Ability to write C++ bindings or integrate Python models into C++, SIMD, and Cuda production pipelines

Benefits

We offer competitive salaries and benefits, an employee stock option grant program, an environment where we are excited to be transforming and disrupting how signal processing is done with AI/ML, a welcoming and inclusive environment, a flexible schedule, and a great work / life balance.

Pay

Competitive salary based on experience and qualifications.

Schedule

Fully remote or on-site in Arlington, VA. Remote option available for the right candidate.