Software Operations Specialist (12 month duration)
Nuro
California
Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future. About The Team Software Operations is where data quality meets real-world impact. Our team reviews annotation outputs, tests the internal tools our engineers rely on, and surfaces the kinds of defects and patterns that, left unchecked, quietly degrade the systems powering our vehicles. We are precise, collaborative, and genuinely motivated by the idea that doing this work well matters. This is a team that takes quality seriously without making it feel like a grind. You will have clear processes to work within, a direct line to the Operations Lead when something needs escalation, and the satisfaction of knowing that the issues you catch and document today help make a self-driving vehicle more reliable tomorrow. About The Role Autonomous vehicles learn from data. The accuracy of that data depends on people who care enough to get every detail right. If that's how you're wired, we want to meet you . We are looking for a Software Operations Specialist for a 12 month term to support quality control, tool testing, and workflow improvement across the internal systems used in robotics and autonomy development. This is a hands-on, execution-focused role and a great place to build deep familiarity with how AI systems are built and validated at a leading autonomy company. You will review software outputs, test internal tools, reproduce issues, and document findings that improve system reliability and team efficiency. The problems you are solving are real: annotation defects that go uncaught can affect model training. Tool bugs that go undocumented can slow down engineering teams. Patterns that go unnoticed can compound quietly until they become something bigger. Your work interrupts all of that. Precision and consistency matter more than speed here. You will apply defined criteria carefully, document every assessment clearly, and escalate anything outside your scope, knowing that your Operations Lead is there to support you. What you bring is rigor, reliability, and a genuine eye for what's off. About The Work Quality Review of Data Annotation
- Review annotated datasets and labeling outputs for quality and consistency across robotics and autonomy workflows.
- Apply defined QC rubrics to evaluate outputs as pass, fail, or needs review, documenting specific defect types clearly: incorrect output, regression, edge-case failure, data inconsistency, or tool behavior deviation.
- Maintain a clean, complete review log for every item assessed. Every assessment is documented. No gaps.
- Test internal tools across standard workflows and exception scenarios as directed by the Operations Lead.
- Reproduce reported bugs reliably and validate fixes with clear supporting documentation including steps taken, inputs used, expected versus actual behavior.
- Track test coverage across tools, workflows, and edge cases, and flag discrepancies before each cycle begins.
- Submit completed QC and testing logs on the agreed cadence, flagging urgent or high-severity defects the same day, without waiting for the regular report.
- Write defect notes that are specific, reproducible, and immediately actionable, not vague flags, but clear descriptions of what failed and why it matters.
- Escalate any case where the rubric or test plan is ambiguous or doesn't cover the scenario. When you're unsure, you ask rather than guess.
- Flag recurring defects, systemic issues, or documentation gaps when you notice patterns across multiple items. Your perspective across the full volume of work is something no one else has.
- Contribute structured feedback to improve QC processes, testing methods, and internal documentation over time.
- Collaborate with operations and engineering teams to communicate findings and support prioritization, routing formal feedback through the Operations Lead.
- 1–3 years of experience in QA, software testing, operations, content review, or a closely related field.
- Demonstrated ability to apply evaluation criteria consistently across high volumes of work without losing precision.
- High attention to detail: you catch what others miss and document it in a way that someone else can immediately act on.
- Clear, specific written communication: defect notes that describe exactly what failed, how to reproduce it, and what the impact is.
- Comfort learning new tools and working across technical systems without needing everything explained upfront.
- Reliable and self-directed: you meet cadences and deadlines consistently without needing to be chased.
- Experience with mapping, 3D tools, or visual software.
- Familiarity with U.S. roadways and driving behavior.
- Experience reviewing outputs across multiple modalities such as text, image, sensor data, or video.
- Exposure to robotics, autonomy, or ML training data production environments.
- Bachelor's degree.
Posted 2026-06-12
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