Cellular Software Enablement Engineer, Wireless Technologies & Ecosystems

Do you want to bring new cellular modems to life inside Apple devices? Do you enjoy working across hardware, firmware, and machine learning to solve problems no one has solved yet? Join us to help deliver the cellular connectivity at the heart of our devices. The Cellular Software & Technologies organization builds and optimizes Apple's in-house cellular software. Within this organization, the Cellular CoreBSP Enablement team brings up firmware on every new cellular modem Apple designs and integrates it into every Apple product that ships with cellular connectivity, from first boot through production readiness and commercialization. We are looking for a hands-on engineer to join this high-visibility team in Santa Clara Valley. This role demands someone who fights for excellence in everything they build, drives what matters by focusing on the highest-impact problems, and fosters trust through transparent communication with partners across the organization.

As a member of the Cellular CoreBSP Enablement team, you will own product bring-up of cellular modems in new Apple devices, from early builds through production readiness, and support bring-up of new modems from pre-silicon emulation through post-silicon hardware. You will lead hands-on debugging across the full hardware and software stack and maintain the device labs and development hardware. You will also develop machine learning models that optimize how cellular firmware runs on the platform, working with data providers and use-case teams from problem definition through on-device deployment.

Demonstrated ability to collaborate across teams, communicate technical information clearly, and drive results with minimal guidance. Hands-on experience debugging embedded systems using JTAG, LLDB, trace tools, or similar. Experience with product, board, or silicon bring-up, including pre-silicon emulation or FPGA platforms. Experience with cellular or wireless modem firmware (LTE, 5G NR). Familiarity with ARM or similar processor architectures. Experience applying machine learning to system performance or efficiency problems, including deploying models on resource-constrained hardware.

BS in Electrical Engineering, Computer Engineering, Computer Science, or a related field, and 2 years of relevant industry experience; or MS in a related field. Proficiency in C/C++ and in Python or other scripting languages, with experience in embedded systems and RTOS environments. Coursework or hands-on experience in machine learning, including training and evaluating models with frameworks such as PyTorch, scikit-learn, or XGBoost.