Staff Software Engineer, Logging

Aurora Innovation•Mountain View, CA

About The Position

Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn . Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We are searching for a Staff Software Engineer to join Aurora’s Logging & Offload team. This team is responsible for Aurora’s self-driving vehicle software stack, focusing on resource-optimized data collection and streamlined wireless data offloading at scale across diverse environments.

Requirements

BS/MS/PhD in Computer Science or related field, or equivalent industry experience
Expert-level C++ programming skills and the ability to design high-performance, thread-safe, and memory-efficient systems in a Linux environment
Proven experience working with storage technologies, block devices, and making informed file system choices based on write endurance, throughput, and crash-consistency constraints
Ability to work across multiple programming languages and paradigms
A passion for writing robust, intuitive, and pragmatic production code.
Ability to navigate and work effectively in large codebases
Strong verbal and written communication skills
Ability to work autonomously and collaborate effectively with colleagues across time zones.

Nice To Haves

Experience with performance evaluation and optimization.
Strong programming skills in GoLang
Experience with safety critical systems

Responsibilities

Design and implement high-throughput, low-latency logging frameworks capable of handling massively parallel data streams
Define smart, dynamic data collection policies (e.g., triggering high-fidelity snapshots during performance events while intelligently downsampling routine driving data)
Evaluate, select, and tune file systems to maximize write speeds and guarantee data integrity
Collaborate with systems and hardware teams to select storage media (NVMe, SSDs) and optimize kernel-level I/O performance.
Work with autonomy engineers to meet performance and efficiency requirements for data collection and offload
Provide engineering support for field testing and fleet operations
Mentor senior engineers, set coding standards, and drive the long-term roadmap for on-vehicle data lifecycle management.