Requirements

• Foundational understanding of OS internals: process and thread lifecycle, virtual memory, scheduling, synchronization, and system calls
• Ability to read and reason through crash reports and kernel panics — backtraces, register state, and basic memory analysis
• Hands-on experience with debugging tools such as LLDB, GDB, or Instruments
• Proficiency in Python for scripting, automation, and test infrastructure

Nice to Haves

• Working knowledge of C and/or Swift for debug tooling or system-level development
• Exposure to automation frameworks, CI/CD pipelines, or scalable test systems
• Experience applying ML or AI techniques to systems problems — crash clustering, log anomaly detection, failure classification, or intelligent alert prioritization
• Familiarity with LLMs or generative AI tooling in an engineering context — prompt engineering, RAG pipelines, or AI-assisted debugging workflows
• Prior coursework or project experience in OS internals, systems programming, or low-level debugging
• Familiarity with Apple platform internals: XNU kernel, Darwin subsystems, IOKit, libdispatch, or dyld
• Contributions to automation frameworks or developer tooling that improved engineering productivity
• Experience or interest in collaborating across silicon, firmware, or platform systems teams
• Enthusiasm for building tools and systems that empower other engineers

What You'll Be Doing

• Digging into the operating system to understand the true origin of crashes and panics
• Encoding triage logic into automation pipelines
• Exploring how ML and AI techniques can make automation pipelines smarter over time
• Collaborating across Software, Hardware, and Silicon Engineering teams to drive issues to resolution