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Wireless Verification Infrastructure Engineer

Apple

Onsite (Sunnyvale, California) Mid Level
Posted 1 week ago

Skills

Python C++ Linux Shell Scripting Distributed Systems Regression Management Automation Frameworks Hardware Verification SoC Development Data Analytics SQL Pandas Jupyter Machine Learning PyTorch TensorFlow

About the Role

Join Apple's Wireless Connectivity team developing state-of-the-art WiFi SoCs that power hundreds of millions of Apple products worldwide. You'll be part of our vertically integrated organization shaping next-gen wireless technology from concept through production. As a Wireless Verification Infrastructure Engineer, you'll ensure first-time-right silicon success through sophisticated testbenches, comprehensive scenarios, and cutting-edge verification methodologies—enabling multi-gigabit wireless technology connecting the world!

Description


As a Wireless Verification Infrastructure Engineer, you'll build and maintain the critical infrastructure that powers our WiFi verification and design efforts. You'll develop regression management systems and automation frameworks that process hundreds of thousands of tests daily across distributed systems. Working closely with Apple / Vendors teams, you'll architect wireless flows, create powerful analytics, and solve high-impact infrastructure challenges—directly accelerating verification closure and enabling the team to deliver exceptional wireless silicon.

Minimum Qualifications


Minimum requirement of a bachelor’s degree. Experience with object-oriented programming and software design principles within Python and C/C++. Experience with distributed systems / compute infrastructure, Linux environments, and shell scripting. Strong problem-solving abilities and debugging approaches.

Preferred Qualifications


Exposure to Hardware / Software Workflows, and/or EDA Tools / Linux environments. Exposure to databases (e.g., SQL), web frameworks, or data analytic tools (Pandas, Jupyter). Exposure to AI coding assistants (Claude Code, Copilot, LLMs) or basic ML frameworks (PyTorch, TensorFlow). Excellent communication and collaboration skills working with partner teams.

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