Staff Software Engineer, Logging (C++)

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$189K-$303K not verified - source not recorded; timestamp not recorded

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

111% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Staff Software Engineer, Logging (C++) Mountain View, California Who we are 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. In this role, you will - 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

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