About the job
About Us
Nuro is a pioneering self-driving technology company dedicated to making autonomous solutions accessible to everyone. Established in 2016, we are developing the most scalable autonomous driver by integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate a variety of applications, including robotaxis, commercial fleets, and personal vehicles. With proven technology from years of self-driving deployments, Nuro provides automakers and mobility platforms with a clear pathway to achieving commercial-scale autonomous vehicles, promoting a safer, more connected future.
Role Overview
At Nuro, we adopt a machine-learning-first strategy in our approach to autonomous driving technology. The performance of our systems is significantly influenced by the quality and diversity of training and evaluation data.
Your team will be pivotal in enhancing our autonomous driving systems by establishing a robust and scalable data infrastructure. This infrastructure will generate training and evaluation data from both real-world driving logs and simulated environments. Collaborating closely with system engineers, you will ensure thorough validation of the autonomous driving system prior to deployment.
Key Responsibilities
- Design and implement cohesive, introspectable data pipelines capable of processing large-scale batch and streaming data across diverse evaluation use cases.
- Develop a storage solution that efficiently manages extensive volumes and a wide variety of performance metrics.
- Create user-friendly dashboards and reports to display evaluation results, enabling easy comparisons to highlight improvements and regressions in ML components and the overall system.
- Establish and maintain continuous testing and monitoring systems to ensure the integrity and robustness of our data and data pipelines.
- Build data mining tools utilizing applied ML techniques to meet data discovery requirements in areas such as Perception, Behavior, and Mapping.
- Develop data annotation tools to aid both first-party and third-party labeling efforts, ensuring high-fidelity perception, mapping, and trajectory labels.
- Scale data annotation labels with cutting-edge ML techniques.
Qualifications
- A degree in Computer Science, Engineering, or a related field (BS, MS, or PhD) combined with at least 4 years of relevant professional experience.
- Strong programming skills in Python or similar languages.
- Experience in data engineering, machine learning, or related fields.
- Familiarity with data pipeline tools and frameworks.
- Ability to work collaboratively in a fast-paced, innovative environment.

