Software Engineer, ML Data Infrastructure

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About the role

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 Role Nuro takes a machine-learning-first approach to autonomous driving technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data. The team plays a crucial role in the advancement of autonomous driving systems by creating a scalable and reliable data infrastructure. This infrastructure is designed to produce training and evaluation data derived from both on-road collected logs and simulation logs. Additionally, the team collaborates closely with system engineers to thoroughly validate the autonomous driving system before its deployment. About the Work • Design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation. • Create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics. • Construct intuitive dashboards and reports to present evaluation results, facilitating straightforward comparisons that highlight both improvements and regressions of the ML components and the overall system. • Develop and maintain continuous testing and monitoring systems to guarantee the integrity and resilience of our data and associated data pipelines. • Develop data mining tools with applied ML techniques to support data discovery needs from Autonomy including Perception, Behavior, and Mapping • Develop data annotation tools to support first-party and third-party labeling workforce to provide high fidelity perception, mapping, and driving trajectory labels • Scale data annotation labels with applied State-of-the-art ML techniques About You • You have a degree in BS, MS.c or Ph.D, plus 1+ years of relevant work experience • Strong proficiency in Python or similar languages • Domain experience: Experience working with large-scale data and building scalable & reliable systems/data pipelines; ability to understand and design complex systems • Technical excellence: Ability and willingness to deep dive into implementation, driving technical standards and best practices across broader software organization • A bachelor's degree in Computer Science, Electrical Engineering, or a closely related field Bonus Points • Strong proficiency in C++ or other high-performance low-level languages • Strong knowledge of GCP, GCS, BigQuery, or PostgreSQL • Knowledge of data engineering, and its tooling and best practices • Knowledge of batch and streaming data processing, warehousing, and analytics solutions • Experience working with large-scale distributed data systems • Experience with system & framework design • Experience with

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