AI-RAN Lead: Wireless ML Architect (Hybrid)

DeepSig Inc; Arlington (VA); Hybrid; USD 140,000 - 230,000; Full time

Benefits offered by this job

Employee stock option

Job summary

DeepSig Inc seeks a Technical Lead to architect and drive AI-native RAN development. You will design, prototype, and validate neural receivers, neural beamforming, and related AI/ML components for real-time deployment on NVIDIA GPUs in an on-site/hybrid setting in Arlington, VA.

Qualified candidates have 3+ years building DL models for signal processing, with strong Python and differentiable-simulation experience. Remote option considered for the right candidate.

Qualifications

• Ph.D. or Master’s in CS, EE, or Applied Math with DL/communications focus.
• 3+ years designing and training deep neural networks.
• Experience applying ML to real-time time-series data or physics-based problems.
• Ability to read papers and implement methods in robust Python code.
• Familiarity with differentiable simulation or digital twins.

Responsibilities

• Design and train DL models for channel estimation, MIMO detection and beam management.
• Build high-fidelity simulations using Sionna and ray-tracing to benchmark models.
• Prototype research models into deployable dApps for the DU with GPU inference.
• Explore AI-RAN frontiers like ISAC, neural scheduling, and channel digital twins.
• Drive IP through invention disclosures, patents, and technical docs.

Skills

Ph.D./Master's in CS/EE/Applied Math

DL/ML model design

Applied signal processing

Research to code

Simulation with differentiable sims

Education

Tools

NVIDIA Sionna

JAX

CUDA

Python

Job description

DeepSig Inc seeks a Technical Lead to architect and drive AI-native RAN development. You will design, prototype, and validate neural receivers, neural beamforming, and related AI/ML components for real-time deployment on NVIDIA GPUs in an on-site/hybrid setting in Arlington, VA.

Qualified candidates have 3+ years building DL models for signal processing, with strong Python and differentiable-simulation experience. Remote option considered for the right candidate.