Wireless PHY Systems Engineer

Apples Wireless SoC team is seeking an exceptional Wireless PHY Systems Engineer to help define the future of wireless technology in Apple products. Our team sits at the forefront of modem architecture physical-layer algorithm research and embedded DSP innovation delivering the wireless capabilities that make AirPods Apple Watch iPhone and other Apple products this role you will drive end-to-end simulation and algorithm development for complex wireless systems spanning Bluetooth and UWB protocol stacks propagation channel modeling RF/antenna behavior and PHY u0026 MAC protocols. You will bring deep technical expertise scientific rigor and a forward-looking perspective including the application of AI/ML methods to solve some of the hardest wireless systems challenges in the role is ideal for those who thrive at the boundary of theory and silicon and who wants their work to reach hundreds of millions of people through world-class consumer products.

As a Wireless PHY Systems Engineer you will lead the research modeling and simulation of sophisticated wireless systems across the full signal chain. You will work at the intersection of algorithm invention system-level analysis and hardware realization collaborating with PHY/algorithm engineers analog and digital designers and firmware/software teams to develop physical-layer features for next-generation SoC will apply AI/ML-driven approaches alongside classical signal processing methods to push the boundaries of simulation fidelity algorithm performance and system understanding. Your work will directly influence chip architecture decisions and the wireless capabilities of future Apple products.

Lead the invention derivation and evaluation of advanced physical-layer algorithms and DSP techniques for Bluetooth UWB and emerging wireless and develop end-to-end simulation frameworks covering propagation channel models RF/antenna abstractions and PHY/MAC protocol with cross-functional teams to model analyze and visualize system performance across the full signal and analyze large volumes of field and simulation data; develop insightful user-friendly visualizations of complex results including measurement accuracies system latencies and protocol performance fixed-point design and RTL vector generation to translate algorithm research into hardware-ready implementations leverage HLS tools where or support lab bring-up and validation activities including FPGA/silicon testing PHY/RF/MAC debugging calibration procedures and advanced lab equipment the team in technical discussions with cross-functional partners and where applicable in external standards bodies or industry AI/ML techniques across all aspects of the role including algorithm design and optimization simulation framework development post-processing and analysis of large-scale field and simulation datasets RF impairment modeling and lab-based bring-up and debugging workflows.

Bachelors degree with 10 years of relevant experience. nStrong systems-level mastery of complex wireless architectures including the ability to reason rigorously about cross-layer dependencies between RF PHY MAC and higher protocol hands-on software programming skills for system modeling and simulation with required proficiency in MATLAB and C/ with fixed-point design and RTL vector collecting processing and visualizing large-scale field and simulation datasets including performance metrics such as measurement accuracy latency and with analog/RF impairments common in wireless systems (e.g. phase noise IQ imbalance nonlinearity).nExperience with or knowledge of wireless standards such as Bluetooth Ultra-Wideband (UWB) or other wireless in lab FPGA/silicon bring-up PHY/RF/MAC testing and use of RF lab equipment.

MSEE/Ph.D. in electrical engineering Digital Communications Signal Processing or equivalent with 10 years of relevant experience applying AI/ML methods to wireless systems such as learned channel estimation AI-driven receiver design neural network-based signal detection or ML-assisted simulation data with Python and data science/ML libraries (e.g. NumPy PyTorch scikit-learn) for simulation automation and AI-assisted analysis with High-Level Synthesis (HLS) tools for algorithm-to-hardware engagement with wireless standards organizations or industry consortia (e.g. IEEE 802.15 Bluetooth SIG FiRa Consortium).nExperience with simulation automation regression frameworks or CI/CD pipelines for large-scale system record of technical publications patents or contributions to the broader wireless research communication skills with the ability to present complex research findings and system trade-offs to diverse technical and non-technical audiences.