Wireless Software Architect (Hybrid)

Cisco•Milpitas, CA

8d•Hybrid

About The Position

We are a focused group of engineers with deep wireless and algorithm expertise, working within a larger organization responsible for Cisco's enterprise Wi-Fi access points. We combine that expertise with strong embedded software engineering, working closely together and moving fast. The problems we solve are real, spanning industries including industrial, medical, and smart office environments, and more. Right now we are actively investing in Wi-Fi 8, device health intelligence, and Edge AI, bringing neural processing directly onto access points to enable real-time network intelligence and next generation physical AI applications.

Requirements

PhD in Engineering or Computer Science with 3+ years of industry experience, or Master's degree with 6+ years.
Strong understanding of Wireless technologies.
Proficiency in C and/or C++ on embedded platforms
Experience with embedded systems, SoC integration, or Linux kernel/driver development
Comfortable working across software and hardware boundaries, from driver and firmware up through cloud platforms

Nice To Haves

Background in Edge AI or embedded ML: on-device inference, model quantization, NPU/DSP acceleration, or real-time ML systems.
Understanding of wireless protocol stacks: 802.11, 802.15.4, BLE
Familiarity with Wi-Fi 7 / Wi-Fi 8 features
Experience using agentic coding tools (Codex, Claude Code, Cursor, Copilot, or similar) and AI assisted development workflows in a production engineering environment.
Strong written and verbal communication; able to explain complex technical concepts across engineering and non-engineering audiences.

Responsibilities

Design and develop next generation enterprise Wi-Fi access point software, focused on performance and reliability at the network edge.
Solve real world wireless challenges across industrial, medical, and smart office deployments, including dense client environments, robotic fleets, and mission critical IoT.
Work on Wi-Fi protocols (802.11ax/be/bn, MLO, OFDMA, MU-MIMO, 6 GHz / AFC), IoT stacks (802.15.4, BLE, Thread, Matter), and radio coexistence in dense, interference heavy environments.
Build and integrate Edge AI capabilities directly on access points using on device NPUs, including model optimization (quantization, pruning), inference frameworks (TFLite, ONNX Runtime), and real time ML pipelines for anomaly detection, RF intelligence, and network assurance.
Work closely with silicon vendors and platform teams to get the most out of advanced Wi-Fi 8 chipsets, including NPU and other offload paths.