AI-RAN Deployment Engineer

DeepSig Inc•Arlington, VA

just now•Hybrid

About The Position

DeepSig Inc. is a venture-backed technology startup focused on revolutionary wireless processing software solutions using machine learning for baseband processing, wireless sensing, and other wireless applications. The AI-RAN Deployment Engineer will be the hands-on link between DeepSig's AI-RAN products and the customers, partners, and test sites that deploy them. This role involves integrating products into customer environments, setting them up at field sites, running tests and demonstrations, and relaying feedback to the engineering team. The position centers on 5G RAN deployment and requires a strong background in radio and SDR, including comfort with RF hardware, software-defined radios, and signal-level debugging. While prior RAN experience is beneficial, it is not strictly required, as a team of RAN and ML specialists will provide support. The day-to-day work focuses on hands-on systems integration, troubleshooting, and optimization.

Requirements

BS in Electrical/Computer Engineering, Computer Science, or related field, or equivalent hands-on experience
4+ years deploying, integrating or supporting radio frequency machine learning, software-defined radio or other RF systems in real environments
Significant hands-on experience with software-defined radios (USRP, Epiq, or similar) and the RF hardware around them: antennas, cabling, filters, amplifiers, power and grounding
Comfortable with RF test equipment and measurement: spectrum analyzers, signal generators, power meters, basic link budget and interference analysis
Working knowledge of wireless systems fundamentals, including OFDM, time and frequency synchronization, and the practical effects of RF impairments on a deployed system
Strong Linux skills: networking, drivers, system configuration, log and packet capture; familiar with programming basics and able to read, run and adapt shell and Python scripts (a software engineering background is not required)
Experience with containers (Docker or Kubernetes) sufficient to deploy, configure and debug containerized software in the field
Willing and able to learn 5G NR and O-RAN deployment on the job: gNB and O-RU configuration, PTP timing, fronthaul, UE attach and basic performance validation
Methodical troubleshooting approach: able to isolate a problem across hardware, RF, timing, network and software layers and document what was found
Strong communication and teaming skills to work directly with customers and partners and collaborate productively in a small company environment
Able to travel to customer sites, test ranges and partner labs; travel varies with deployment schedules and can peak at 25 percent during installs and test events

Nice To Haves

Prior experience deploying or operating 5G NR, LTE or O-RAN systems (srsRAN, OCUDU, OAI, or commercial gNBs), including PTP/SyncE timing chains and eCPRI fronthaul
Familiarity with GNU Radio or similar SDR frameworks and with IQ data capture and analysis workflows
Experience with NVIDIA GPU platforms in deployed systems: driver and container runtime setup, Kubernetes and Helm
Exposure to machine learning for RF (spectrum sensing, signal classification) and to collecting and labeling RF datasets
Field experience with CBRS, private 5G or tactical communications deployments, including spectrum coordination and site RF surveys
Experience with vendor O-RUs and radio hardware integration (Foxconn, WNC, Eridan or similar)
Python or C++ experience beyond scripting, for building test and automation tooling

Responsibilities

Own customer and partner integrations of DeepSig software end to end: scoping the deployment, configuring radios, timing and networking, installing and configuring the OCUDU stack and dApps, and carrying the system through acceptance
Plan and execute site visits: pre-visit surveys and bills of material, on-site installation and bring-up, over-the-air validation, and on-site support during test events and demonstrations
Bring up and troubleshoot deployed systems across the whole chain, from antennas, cabling and RF front ends through SDR and O-RU hardware, timing and fronthaul, to the software stack and the dApps running on it
Capture and analyze RF data in the field (IQ recordings, spectrum sweeps, link measurements) to validate performance, debug issues and feed datasets back to the ML team
Reproduce field issues in the lab, isolate them to a subsystem and hand well-characterized defects to the owning software, RAN or ML engineer
Write and maintain deployment procedures, configuration baselines, site documentation and runbooks so that installs are repeatable and supportable by others
Build and maintain lab test setups and integration benches alongside the lab engineer, including interoperability testing with partner radios, UEs and test equipment
Act as a technical point of contact for customers and partners during integration, translating their requirements and constraints into clear asks for the engineering team
Support product managers and business development with demonstrations, trial deployments and customer feedback on deployability and operability