Job description

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. 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. Tool Testing and Bug Reproduction 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. Reporting and Escalation 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. Pattern Recognition and Process Improvement 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. About You You are the kind of person who notices things others miss, taking the time to document them clearly rather than move on. You find satisfaction in applied consistency: applying a rubric the same way on item 1 and item 200, and catching the edge case that slipped by. You want your work to connect to something larger, and you're ready to build deep expertise in a domain that's shaping the future of how people move. What You Bring 1–3 years of experience in QA, software testing, operations, content review, or a closely related field. Familiarity with U.S. roadways and driving behavior. 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. Bonus Points Experience with mapping, 3D tools, or visual software. 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. At Nuro, your base pay is one part of your total compensation package. For this position the reasonably expected annualized base salary range is $87,000- $118,000. Offers are based on an individual’s experience, education, location, and skills. This is a temporary position of a 12 month duration. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-CD1

Requirements

Must-haves

About the Team
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 .
1–3 years of experience in QA, software testing, operations, content review, or a closely related field.
Familiarity with U.S. roadways and driving behavior.
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.

Nice-to-haves

Experience with mapping, 3D tools, or visual software.
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.

Application prep

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