Machine Learning Signal Processing Engineer

Overview

Deep Sig 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). Deep Sig 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 3

GPP 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.

• AI-RAN Algorithm and Software-Module Development:
  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.
• AI-RAN Algorithm and Software-Module Development:
  Contribute to algorithm optimizations for MU-MIMO/mMIMO optimization functions (e.g. user-pairing, prediction, beamforming, etc.).
• AI-RAN Algorithm and Software-Module Development:
  Build reference ML module interfaces (data capture, online inference, scoring/benchmarking, simulation, performance validation) to integrate into RAN software stacks.

• Dataset & Training Infrastructure:
  Develop measurement and dataset collection tools and pipelines for training and scoring AI-RAN models and performance.
• Dataset & Training Infrastructure:
  Build model training and KPI benchmarking tools for reproducible comparison across models and use cases and interoperable model testing.
• Dataset & Training Infrastructure:
  Lead and contribute to commercial and open-source software for NextG AI-RAN capabilities.

• Accelerated Compute Functions:
  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.
• Accelerated Compute Functions:
  Explore model compression, quantization, and deployment on specialized accelerators.

• Integration & Interoperability:
  Work with O-DU stacks (FlexRAN, OAI, SRS, Aerial) to integrate & benchmark AI-RAN modules.
• Integration & Interoperability:
  Ensure interoperability through open data interfaces that allow model insertion, data collection, performance measurement, and comparison across multiple parties.

• Research &
  
  Collaboration:
  
  Stay current on the latest ML and wireless research; assess applicability to 3
  
  GPP AI-RAN and ISAC use cases, contributing to research, development, and standardization efforts.
• Research &
  
  Collaboration:
  
  Collaborate with internal product teams and external partners (AI-RAN Alliance, 3
  
  GPP studies, OpenRAN Alliance) to drive adoption of AI-RAN modules and publish findings.
• Research &
  
  Collaboration:
  
  Contribute to publications, standardization, research items, conferences, and open-source software aligned with the OpenRAN and the Open AI-RAN vision.

• 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, Tensor Flow)
• 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…