Machine Learning Signal Processing Engineer

DeepSig Inc • Arlington, VA

78d

About The Position

DeepSig Inc. is a venture-backed technology company pioneering the use of AI in wireless applications (physical layer communications, sensing, and others) by replacing traditional signal processing with algorithms derived by machine-learning (ML). DeepSig software products are achieving significant performance increases while reducing power consumption, which brings significant value to our customers. We are seeking engineers with strong expertise at the intersection of machine learning, wireless signal processing/DSP, and 3GPP standards. This role will support AI-RAN component development for next-generation RAN systems, including development of AI-RAN reference designs, optimized algorithms and implementations, dataset and training pipelines, input into 6G study items, and accelerated compute functions. You will work on both fundamental ML-for-PHY/AI-COMMS problems and software integration into RAN stacks, contributing to both open and commercial components, and interoperable, and high-impact next generation wireless systems.

Requirements

• BS, MS, or PhD in Electrical/Computer Engineering, Computer Science, or related field.
• Proficiency in at least one programming language (Python or C++ preferred).
• Familiarity with Deep Learning frameworks (e.g. – PyTorch, TensorFlow).
• Experience in some of the following areas: deep learning, RF Sensing, statistical signal processing/DSP, wireless/communications systems fundamentals, time/frequency analysis of signals, machine learning, channel estimation and equalization, MIMO systems, beamforming.
• Ability to work on open-ended and self-guided problems, building candidate solutions and coming up with appropriate metrics for comparison, system designs, and rigorous customer centric validation.
• Strong communication and teaming skills to work collaboratively and productively in a small company environment.

Nice To Haves

• Experience in building machine learning models optimized for deployment hardware platforms.
• Familiarity with communications systems and/or 3GPP 5G NR physical layer and ORAN architecture.
• Background in digital signal processing (multi-rate, polyphase filters, equalization, synchronization).
• Experience in building & optimization ML / Deep Learning models for efficient deployment.
• Familiarity with widely used SW ML tools such as C++, CUDA, TensorRT, OpenCL, ONNX, etc.
• Experience in edge deployment of ML models and accelerator toolchains (TensorRT, CUDA, ONNX, Ryzen-AI, OpenCL, oneDNN, FPGA/AI implementation, etc).
• Prior work with Sionna PHY/RT, MATLAB, and other link and system level wireless tools/sims.
• Contributions to communications software or standards (e.g., AI-RAN Alliance, 3GPP, IEEE, etc.).

Responsibilities

• Design and implement AI/ML models for multiple key RAN functions including receivers, spectrum sensing, ISAC/active sensing, schedule and resource optimization, and other use cases.
• Contribute to algorithm optimizations for MU-MIMO/mMIMO optimization functions (e.g. user-pairing, prediction, beamforming, etc.).
• Build reference ML module interfaces (data capture, online inference, scoring/benchmarking, simulation, performance validation) to integrate into RAN software stacks.
• Develop measurement and dataset collection tools and pipelines for training and scoring AI-RAN models and performance.
• Build model training and KPI benchmarking tools for reproducible comparison across models and use cases and interoperable model testing.
• Lead and contribute to commercial and open-source software for NextG AI-RAN capabilities.
• Implement and optimize critical baseband and AI/ML algorithms on accelerated compute platforms (e.g. GPU, NPU, TPU) with an emphasis on real-time deployment, latency, energy.
• Explore model compression, quantization, and deployment on specialized accelerators.
• Work with O-DU stacks (FlexRAN, OAI, SRS, Aerial) to integrate & benchmark AI-RAN modules.
• Ensure interoperability through open data interfaces that allow model insertion, data collection, performance measurement, and comparison across multiple parties.
• Stay current on the latest ML and wireless research; assess applicability to 3GPP AI-RAN and ISAC use cases, contributing to research, development, and standardization efforts.
• Collaborate with internal product teams and external partners (AI-RAN Alliance, 3GPP studies, OpenRAN Alliance) to drive adoption of AI-RAN modules and publish findings.
• Contribute to publications, standardization, research items, conferences, and open-source software aligned with the OpenRAN and the Open AI-RAN vision.

Benefits

• Competitive salaries and benefits.
• Employee stock option grant program.
• Flexible schedule.
• Great work/life balance.
• Collaborative, agile, and fun small-team culture.
• Encouragement of participation in scientific publications, conferences, and open-source software.

What This Job Offers

• Career Level: Entry Level
• Education Level: Master's degree
• Number of Employees: 11-50 employees