Description
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 designs. You 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.
Minimum Qualifications
Bachelor’s degree with 10+ years of relevant experience. Strong systems-level mastery of complex wireless architectures, including the ability to reason rigorously about cross-layer dependencies between RF, PHY, MAC, and higher protocol layers. Extensive hands-on software programming skills for system modeling and simulation, with required proficiency in MATLAB and C/C++. Experience with fixed-point design and RTL vector generation. Experience collecting, processing, and visualizing large-scale field and simulation datasets, including performance metrics such as measurement accuracy, latency, and throughput. Familiarity with analog/RF impairments common in wireless systems (e.g., phase noise, IQ imbalance, nonlinearity). Experience with or knowledge of wireless standards such as Bluetooth, Ultra-Wideband (UWB), or other wireless protocols. Experience in lab FPGA/silicon bring-up, PHY/RF/MAC testing, and use of RF lab equipment.
Preferred Qualifications
MSEE/Ph.D. in electrical engineering, Digital Communications, Signal Processing, or equivalent with 10+ years of relevant experience. Demonstrated 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 analysis. Proficiency with Python and data science/ML libraries (e.g., NumPy, PyTorch, scikit-learn) for simulation automation and AI-assisted analysis workflows. Experience with High-Level Synthesis (HLS) tools for algorithm-to-hardware translation. Prior engagement with wireless standards organizations or industry consortia (e.g., IEEE 802.15, Bluetooth SIG, FiRa Consortium). Experience with simulation automation, regression frameworks, or CI/CD pipelines for large-scale system simulation. Track record of technical publications, patents, or contributions to the broader wireless research community. Exceptional communication skills with the ability to present complex research findings and system trade-offs to diverse technical and non-technical audiences.
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