RF Datapath Correction Algorithms - Engineering Intern/Co-op (M/F/D)

dge, real-world challenges, and contribute to the core technology that powers Apple's wireless products.
Join our team of leading experts and help us explore how AI can redefine the performance and efficiency of the RF systems that connect our customers to the world.

Description
In this role, you will be an integral part of our RF Receiver Systems team, focusing on the research and application of algorithms for signal impairment compensation
Your work will include the following tasks:
Analyze state-of-art technology and propose new innovative solutions for RF signal path challenges such as IQ mismatch compensation, online calibration, digital post distortion and other correction techniques etc.
Research, design, and prototype machine learning models-including neural networks and reinforcement learning
Develop and maintain simulation environments in Python or MATLAB to model RF systems and test algorithms
Analyze simulation and measurement data to evaluate model performance, identify trade-offs, and propose improvements.
Collaborate with senior engineers to understand system requirements and translate them into model objectives and constraints.
Document your findings, create presentations, and share your results and insights with the broader team.

Preferred Qualifications
Currently pursuing an MS or PhD with a focus on communications or RF systems.
Demonstrated experience through projects (academic or personal) applying ML to engineering problems, especially in the wireless or signal processing domain.
Familiarity with cellular communication standards (e.g., 5G NR, LTE) and RF transmitter concepts (e.g., power amplifiers, linearity, digital pre-distortion).
A passion for building things and a desire to make a tangible impact on future Apple products.

Minimum Qualifications
Currently enrolled in a BS, MS, or PhD program in Electrical Engineering, Computer Science, or a related field.
Foundational coursework in RF/microwave engineering, wireless communications, and digital signal processing.
Solid theoretical understanding of machine learning, including neural networks and reinforcement learning concepts.
Proficiency in Python and experience with common ML libraries
Strong analytical and problem-solving skills with an eagerness to learn and take on new challenges.
Excellent communication and collaboration skills.

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.