Sr. / Staff Software Engineer, Infrastructure (Autonomy)
About The Position
DiDi Autonomous Driving is seeking an experienced Senior or Staff Software Engineer, Infrastructure, to lead the architecture and evolution of the core platform powering its autonomous driving software stack. The role defines the technical roadmap for high-performance middleware, custom compiler infrastructure including ccatch, onboard toolchains, and large-scale simulation frameworks such as ezsim and automated crash triage. The engineer will collaborate with Autonomy and Simulation teams to improve platform stability, establish engineering standards, and increase developer productivity across teams. The role also provides technical leadership through mentoring, design reviews, and foundational architecture guidance.
Requirements
- Bachelor’s or higher degree in Computer Science, Computer Engineering, Software Engineering, or a closely related technical field.
- 6–10+ years of software engineering experience designing, architecting, and maintaining complex real-time systems, Linux systems infrastructure, or autonomous driving platforms in C++.
- Proven technical leadership and system architecture experience, including driving complex, multi-team engineering initiatives from inception through production deployment.
- Expert-level understanding of C++, systems programming, multithreading, concurrency models, and low-latency IPC or middleware architectures.
- Deep knowledge of compiler internals such as Clang/GCC and LLVM; build systems such as Bazel/CMake; and compilation optimization tools, including caching systems like ccatch.
- Ability to debug complex system-level faults, kernel and user-space crashes, memory corruption, and race conditions.
Nice To Haves
- Experience architecting or extending simulation execution platforms such as ezsim, evaluation frameworks, and automated crash-triage pipelines for robotics or autonomous driving.
- Expertise in embedded systems, cross-compilation target setups such as QNX, Linux RT, or NVIDIA Orin, and hardware acceleration layer integrations.
- Experience with low-level systems profiling tools such as eBPF or gperf, customized memory allocators, or custom IPC protocol design.
- History of building developer productivity tools, developing quantitative software evaluation metrics, and driving root-cause analysis in complex robotic environments.
Responsibilities
- Lead the architectural vision, design, and implementation of low-latency, high-throughput IPC messaging middleware and runtime execution engines for onboard systems.
- Own build infrastructure, toolchains, and compiler execution strategies, including ccatch and distributed build caching, to improve developer velocity and software deployment pipelines.
- Architect deterministic simulation platforms such as ezsim and develop automated diagnostic toolchains for simulator crash triage, core dump analysis, and systemic fault isolation.
- Drive cross-functional performance profiling, memory optimization, and latency reductions across the autonomous driving software stack on embedded hardware.
- Advise onboard teams on software design for efficiency, flexibility, scalability, and reliability across the autonomy stack.
- Improve internal development tools, diagnostic systems, and engineering workflows while managing system complexity and runtime stability.
- Mentor engineers, set engineering standards, lead technical design reviews, and establish architecture guidelines across cross-functional teams.
Benefits
- Bonus
- Equity
- Benefits
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
