Location
London

Hours
Full Time

Salary
Negotiable

About the Role
The Triage Intelligence and Debug Engineering team operates at the deepest layers of Apple's software stack, with a mandate spanning the entire product ecosystem. The work directly shapes the reliability of over 2 billion active Apple devices — every crash triaged, every panic root-caused, and every automated pipeline built contributes to the OS stability that hundreds of millions depend on daily. You will partner closely with engineering teams across Apple to drive reliability end-to-end, influencing how the organization detects, understands, and resolves systemic failures.

We are seeking a curious and motivated Software Engineer passionate about OS internals, automation, and intelligent systems. Your investigations will uncover failures affecting Apple’s entire device ecosystem, with contributions touching software running across iPhone, Mac, and Apple Silicon. The automation pipelines you help build will shape how reliability engineering scales across Apple.

You will dig into the operating system to understand the true origin of crashes and panics — not just the symptom at the top of a stack trace, but the underlying system-level conditions that caused it. You will operationalize that understanding by encoding triage logic into automation pipelines and explore how ML and AI techniques can make those pipelines smarter over time. Collaboration across Software, Hardware, and Silicon Engineering teams is key to driving issues to resolution.

This role is ideal for an engineer eager to learn deep OS internals, excited to build scalable automation and intelligent tooling, and motivated by seeing their work have real, measurable impact.

Experience
- Triage crashes and panics across Apple’s OS stack by analyzing crash logs, kernel panics, and core dumps to isolate root cause
- Collaborate with Software, Hardware, and Silicon teams to propose fixes, close coverage gaps, and drive issues to resolution
- Encode triage logic into automation pipelines for automated classification and escalation
- Apply ML and AI techniques such as crash clustering, anomaly detection, and pattern recognition to build smarter triage pipelines
- Build debug tooling, scripts, and CI/CD integrations that surface OS-level signals and validate platform stability at scale
- Hands-on experience with debugging tools like LLDB, GDB, or Instruments
- Proficiency in Python for scripting, automation, and test infrastructure
- 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
- Familiarity with LLMs or generative AI tooling in engineering contexts such as 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 including 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

About you
Enthusiastic about building tools and systems that empower other engineers. Eager to learn how operating systems work at a deep level. Motivated by creating scalable automation and intelligent tooling. Strong collaborator across multiple engineering disciplines. Passionate about improving software reliability and stability at scale.

Qualifications
Foundational understanding of OS internals including process and thread lifecycle, virtual memory, scheduling, synchronization, and system calls. Ability to read and reason through crash reports and kernel panics including backtraces, register state, and basic memory analysis.