Senior Wireless Machine Learning Engineer, AI-RAN

Socket.dev; Arlington (VA); Hybrid; USD 170,000 - 230,000; Full time

Job summary

DeepSig is seeking an experienced Technical Lead to architect and drive AI-native RAN development. You will design, prototype, and validate neural receivers, neural beamforming, neural scheduling, and ISAC features, pushing the frontier of AI-enabled wireless systems.

You will build simulations, train models with NVIDIA Sionna, and translate research into deployable components for real-time inference on GPU hardware. Collaboration across teams and IP-focused work are expected.

Qualifications

• Education: Ph.D. or Master’s in Computer Science, Electrical Engineering, or Applied Mathematics with a focus on Deep Learning and/or Communications Systems.
• AI/ML Expertise: 3+ years of experience designing and training deep neural networks from scratch; strong architectures and optimization knowledge.
• Applied Signal Processing: Experience applying ML to real-time time-series data, signal processing, or physics-based problems (RF/communications).
• Research to Code: Ability to read papers and implement methods in robust Python code.
• Simulation Skills: Differentiable simulation or digital twins (Sionna, JAX-based sims).

Responsibilities

• Applied AI Research: Design and train modern deep learning models to solve complex physical layer problems (channel estimation, MIMO detection, beam management).
• Simulation & Validation: Build high-fidelity link-level simulations to train and benchmark AI models against baselines.
• Prototyping & Deployment: Transition models into deployable dApps for the DU, optimize latency and compute on NVIDIA GPUs.
• New Capabilities: Explore ISAC, neural scheduling, and channel digital twins.
• Innovation & IP: Author invention disclosures, filing patents, and generate technical reports for 3GPP/O-RAN contributions.
• Data Engineering: Architect data pipelines for synthetic datasets and Sim-to-Real transfer.

Skills

Deep Learning

ML for wireless

Python

C++

Education

Ph.D. in CS/EE/Applied Math

Master’s in related field

Tools

NVIDIA Sionna

JAX

Job description

Description

Type: Full-Time(W2) On-site/Hybrid, Arlington, VA (Remote option available for the right candidate)

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.

In this role, you will design, prototype, and validate novel AI/ML components—such as neural receivers, neural beamforming, neural scheduling, digital twin, and ISAC (Integrated Sensing and Communications)—that outperform traditional signal processing methods. You will work at the cutting edge of 6G innovation, taking concepts from mathematical intuition to simulation (e.g. NVIDIA Sionna) and real-time implementation.

What You’ll be Doing

• Applied AI Research: 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
• Simulation & Validation: Build high-fidelity link-level simulations using NVIDIA Sionna and ray-tracing to train, test, and benchmark AI models against legacy 5G baselines
• Prototyping & Deployment: Transition research models into deployable "dApps" for the Distributed Unit (DU), optimizing inference for latency and compute efficiency on NVIDIA GPUs
• New Capabilities: Explore emerging AI-RAN frontiers such as Integrated Sensing and Communications (ISAC), neural scheduling, and channel digital twins
• Innovation & IPR: 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
• Data Engineering: Architect data pipelines for generating synthetic training datasets and developing "Sim-to-Real" transfer techniques to ensure robust performance in real-world networks

Required Qualifications

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

Preferred Qualifications

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

Working at DeepSig

DeepSig is growing its technical team while cultivating a collaborative, agile, and fun small-team culture. We value creativity, knowledge sharing, and employee growth, and we encourage participation in scientific publications, conferences, and open-source software. 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.

DeepSig is an equal-opportunity employer and does not discriminate based on race, ethnicity, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. We are dedicated to cultivating an inclusive, diverse, and engaging workplace where individuals feel fulfilled, inspired, and motivated. We value the unique perspectives that our team brings.