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Apple

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

22 days ago• Munich, Germany

About us

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

★ 3.7 out of 5 · 120 reviews

  • Size: 10,000+ employees
  • Industry: Technology: Manufacturing
View company profile ›

Why you should apply for a job to Apple:

  • Ranked as one of the Best Technology Companies in 2020
  • 3.7/5 in overall job satisfaction
  • 3.1/5 in supportive management
  • 66% say women are treated fairly and equally to men
  • 65% would recommend this company to other women
  • 66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

At Apple, we work every single day to craft products that enrich people's lives. The people here at Apple don't just create products - they create the kind of wonder that revolutionizes entire industries. We invite you to join our dynamic group, for the unique and rewarding opportunity to contribute to upcoming products that will delight and inspire millions of Apple's customers every day.

Are you interested in doing work that challenges you, expands your thinking, provides innovative solutions for future problems while driving your growth as recognized technical leader in the cellular industry? Apple's RF Transmitter Systems Engineering team is looking for a passionate, talented individual who is eager to break technical boundaries and to change the way of doing things. Our elite team is shaping the mobile market with disruptive RF innovations while taking full responsibility for execution and commitments to schedule and quality.
Join our team of leading experts in cellular RF industry and deliver differentiating transmit architectures and solutions for Apple's wireless products that create amazing value for our customers!

Description
In this role, you will be part of an industry-leading RF Transmitter Systems Engineering team. You will work closely with other architecture- and systems engineering teams, RF design teams and SW teams to assess, specify and drive transmitter concepts with focus on leading-edge performance and uncompromised quality as baseline for differentiating products.","responsibilities":"Your daily work includes the following tasks:
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.

Preferred Qualifications
Initial expertise in transmitter system-level concepts and control procedures like 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.

Minimum 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.

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Additional Information

  • Posted: 22 days ago
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