Sr. / Staff Software Engineer, Infrastructure (Autonomy)

DiDi Labs•San Jose, CA

4d•$169,783 - $338,694

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 closely with Autonomy and Simulation teams to improve platform stability, establish engineering standards, and increase cross-team developer productivity. The position also provides technical leadership across teams, with responsibility for architecture, performance, reliability, developer tools, and engineering practices.

Requirements

Bachelor’s degree or higher 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++.
Demonstrated technical leadership, system architecture experience, and ability to drive 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 such as 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 core simulation execution platforms such as ezsim, evaluation frameworks, and automated crash-triage pipelines for robotics or autonomous driving.
Expertise in embedded systems, cross-compilation targets 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.
A history of building developer productivity tools, developing quantitative software evaluation metrics, and driving root-cause analysis in complex robotic environments.

Responsibilities

Lead the architecture, design, and implementation of next-generation, 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 post-mortem diagnostic toolchains for simulator crash triage, core dump analysis, and fault isolation.
Lead cross-functional performance profiling, memory optimization, and latency reduction across the autonomous driving software stack on embedded hardware.
Advise onboard teams on software design to improve 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.