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Apple's RF Transmitter Systems Engineering team is seeking a senior systems engineer to design and develop next-generation cellular RF transmitter architectures for Apple's wireless products. You will work at the intersection of RF systems engineering and machine learning, translating system-level performance requirements into specifications for transmitter line-ups, RF algorithms, and control infrastructure.
Key Responsibilities:
- Translate system-level and performance requirements into TX line-up and TX feature specifications, including RF algorithm specifications for RFICs and system firmware
- Understand and specify RF algorithms (power control, calibration) and define RF control infrastructure, including compute resources, interfaces, memory, and timing constraints
- Research, design, and prototype machine learning models—including neural networks and reinforcement learning—for RF transmitter applications such as power control, calibration, and digital pre-distortion
- Develop and maintain simulation environments in Python or MATLAB to model RF systems and test AI algorithms
- Analyze simulation data to evaluate model performance, identify trade-offs, and propose improvements
- Collaborate with architecture, systems engineering, RF design, and software teams across global, multicultural groups
You will be part of an elite team shaping the mobile market with disruptive RF innovations, taking full responsibility for execution and commitments to schedule and quality.
Requirements:
- Proven years of relevant experience in RF, including cellular transmit architectures, OR PhD degree with previous work on cellular topics
- Knowledge of cellular radio/3GPP standards (GSM, UMTS, LTE, LTE-A, 5G NR), including RF aspects, system use cases, and TX waveforms
- Familiarity with RF systems and transceiver architecture, including lineup design and component-level trade-offs (gain, linearity, noise, power, thermal)
- Solid theoretical grounding and hands-on experience with classical machine learning techniques (clustering, dimensionality reduction) applied to regression and classification problems
- Solid theoretical understanding and hands-on experience with neural networks for regression and classification problems
- Practical experience across supervised, unsupervised, and reinforcement learning
- Strong analytical skills and ability to collaborate across multicultural, global teams
- BSEE or MSEE degree
- Proficiency in English
Preferred Qualifications:
- Initial expertise in transmitter system-level concepts and control procedures (power control, digital predistortion, envelope tracking)
- Background in digital signal processing
- Understanding of SoC integration constraints and multi-chip RF architectures
- Ph.D. in Electrical Engineering or equivalent
