Senior or Staff Software Engineer — QAIRT Windows Platform

优缺点分析

角色解读

• Progress to Staff/Principal Engineer architecting next-gen SDK components or leading major platform initiatives.
• Move into technical leadership roles managing a sub-team or driving cross-team engineering efforts.
• Transition to AI/ML systems architecture or platform engineering roles at other top tech companies.
• Develop and maintain the QAIRT SDK on Windows on Snapdragon, covering the full stack from user-facing APIs to hardware backend.
• Investigate and fix runtime failures, performance regressions, and inference accuracy issues in production and integration.
• Design SDK components for long-term compatibility across evolving Windows versions, SoC drivers, and applications.
• Collaborate with global hardware and software teams to drive technical decisions and architectural improvements.
• Strong C/C++ proficiency with deep Windows platform development experience.
• Expertise in system-level debugging and performance profiling using tools like WinDbg.
• Understanding of AI inference frameworks (PyTorch, ONNX Runtime) and deployment pipelines.
• Solid foundation in API design, versioning, and cross-component compatibility.

申请策略

• Tailor your cover letter to show enthusiasm for on-device AI and long-term software engineering discipline.
• Prepare to discuss a past project where you owned a complex system from end to end.
• Emphasize experience with Windows system-level development, especially in C/C++ and debugging.
• Highlight any work on SDKs, runtime libraries, or APIs where compatibility and stability were key.
• Showcase AI/ML inference deployment or performance optimization (PyTorch, ONNX Runtime).
• Include examples of solving complex cross-layer bugs or versioning issues.
• Deepen knowledge of Windows internals, especially DLL loading and versioning mechanisms.
• Get hands-on with WinDbg and other Windows diagnostic tools to improve debugging efficiency.

面试指南

• Use the STAR method (Situation, Task, Action, Result) for behavioral questions, focusing on your technical reasoning.
• For design questions, start by stating requirements (compatibility, performance, extensibility), then propose a layered architecture with clear versioning contracts.
• For debugging questions, describe a systematic approach: reproduce, isolate layers, use tools, hypothesize, test.
• How would you design an API for a runtime inference SDK that needs to remain compatible across future Windows and driver versions?
• Walk us through a time you debugged a system-level crash that involved multiple components. What was your process?
• Explain how you would test compatibility when you cannot test every possible combination of SDK, driver, and OS versions.
• Given a performance regression in an inference pipeline, how would you isolate the bottleneck?
• How do you balance feature development with maintaining long-term stability and compatibility?