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.