Senior Wireless Machine Learning Engineer, AI-RAN

DeepSig, Inc.; Arlington, Northern (VA, KY); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Stock option plan

Flexible schedule

Work-life balance

Job summary

DeepSig is seeking an experienced Technical Lead to architect and drive AI-native RAN development in Arlington, VA. You will design, prototype, and validate AI/ML components such as neural receivers, neural beamforming, and digital twins, taking concepts from theory to real-time implementation on NVIDIA GPUs.

Join a small, collaborative team that values innovation, open publications, and patents. The role blends research, prototyping, and deployment with a path toward leadership and impact in 6G

Qualifications

• Ph.D. or Master's in CS, EE, or applied math with focus on DL or communications.
• 3+ years designing and training deep neural networks from scratch.
• Experience applying ML to real-time time-series data and physics-based problems.
• Ability to read papers and implement methods in Python.
• Experience with differentiable simulation or digital twins (e.g., Sionna, JAX-based sims).

Responsibilities

• Applied AI research: Design and train deep learning models for channel estimation, MIMO detection, and beam management.
• Simulation & validation: Build high-fidelity link-level simulations to benchmark AI models against baselines.
• Prototyping & deployment: Translate research to deployable dApps for the DU, optimize latency and compute.
• New capabilities: Explore ISAC, neural scheduling, and neural channel digital twins.
• Innovation & IP: Author invention disclosures and support patent filings.
• Data engineering: Architect data pipelines for synthetic training data and sim-to-real transfer.

Skills

Deep Learning Architectures

Time-series ML for signal processing

Python

Research to Code

Model optimization

Education

Ph.D. or Master’s in CS/EE/Applied Math focusing on DL or Communications

Tools

TensorRT

CUDA

C++ Bindings

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.