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Cellular RF Transmitter Systems Engineer (m/f/d)

Apple· Hardware
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MunichFull-timePosted 2mo ago

About the role

Apple’s RF Transmitter Systems Engineering team seeks a passionate engineer to design and deliver differentiating cellular transmitter architectures and solutions for Apple’s wireless products, collaborating with architecture, RF design, and software teams to translate requirements into TX line-up features and RF algorithms, while researching and prototyping ML approaches for power control, calibration, and digital pre-distortion.

Responsibilities

  • Translate system-level and performance requirements into requirements for the TX line-up and TX features, including RF algorithm specifications for RFICs and system firmware.
  • Understand and specify RF algorithms (e.g. power control, calibration) and define the 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.

Qualifications

  • 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 as well as system use cases and TX waveforms.
  • Familiarity with RF systems and transceiver architecture, including lineup design and component-level trade-offs (e.g. gain, linearity, noise, power, thermal).
  • Solid theoretical grounding and hands-on experience with classical machine learning techniques (e.g., 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 the ability to collaborate and communicate across multicultural, global teams.
  • BSEE or MSEE.
  • Proficiency in English.

Skills

Required:RF transmitter architecturesRF algorithmsMachine learning for RFSimulation toolsStandards knowledgeCommunication & collaboration
Last updated Oct 23, 2026. Interested? Apply on the company site.

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