Receiver RF Silicon Validation Engineer (m/f/d)
Job details
- Education
- Master's degree
- Posted
- Nov 4, 2026
- Last confirmed open
- Nov 4, 2026
What you'll need to apply
What this employer's standard application typically asks
Company-specific questions
- Have you previously worked at Apple?
About this role
Imagine what you could do here. At Apple, new ideas quickly become extraordinary products, services, and customer experiences. Bring passion and dedication to your job, and there's no telling what you could accomplish.
Smart people and inspiring, innovative technologies are the norm here.
Our team is responsible for validating the RF performance of top-notch, monolithic, cellular transceivers and the RF subsystems built around them. In order to expand our team's validation capability towards future Apple products, we are looking for a passionate RF engineer with strong RF transceiver system understanding, complemented by AI/ML and programming skills.
The world-class cellular RF sub-systems developed in our labs are enabling Apple mobile devices to deliver uncompromised cellular network connectivity at the lowest possible battery drain, enabling long hours of an enjoyable customer experience.
Thus, join us and leverage your passion for RF excellence and innovation, bringing your advanced education and drive to the world's most innovative company!
In the position of Receiver RF Silicon Validation Engineer, you will work on market-leading, cutting-edge cellular transceivers.
The broad scope of responsibilities includes definition of test strategy and test plan creation derived from receiver system specification, characterization, and optimization of key RF parameters, the analysis of functional or performance issues encountered during different verification phases, and the development of scripts for test automation.
You will work in an agentic engineering flow — scoping the problem and defining pass/fail criteria, delegating implementation and execution to AI agents, and verifying every result against the specification — applying innovative AI/ML-based methods to advance our measurement and analysis capabilities and to scale our regression environment.
Your work style is very collaborative; you manage your deliveries and dependencies self-contained, and your execution enables you to meet your commitments.
Master’s degree in electrical engineering, Communication/ Embedded Systems, or equivalent paired with several years of relevant industry work experience
- In-depth knowledge of RF fundamentals and RF measurement techniques
- Working knowledge of AI/ML, able to apply AI/ML methods to achieve results, with a solid grasp of the fundamentals
- Programming skills, leveraging modern AI-coding assistants to generate scripts, debug logic, and optimize code, with languages such as Python, C/C++, and MATLAB
- English language proficiency is required for this position
- PhD in Electrical Engineering, Communication/ Embedded Systems, or equivalent; industrial RF silicon-validation experience (e.g., internship, working student or industry project) is a plus
- Familiarity with RF transceiver system definition and architecture, including RF impairments (e.g., I/Q imbalance, DC offset, phase noise, nonlinearity) and their impact on receiver performance — ability to derive validation strategy, test plans, and pass/fail criteria from system specifications
- Knowledge of 3GPP standards with a focus on RF transceiver aspects and receiver RF requirements
- Hands-on experience applying AI/ML techniques and agentic engineering (delegating tasks to AI agents and verifying their output) to RF, signal-processing, or lab-automation problems
- Hands-on experience (from PhD work, thesis, internships or industry) in characterizing and debugging RF cellular systems and components, including root cause analysis, and in creating test automation scripts to run in the lab and/or regression environment
- Ability to collaborate technically with a variety of teams (Design, Firmware, System, etc.)
- Team spirit, excellent communication skills, and the desire to accept diverse challenges are essential