Software Engineer, ML Data Infrastructure

Overview In this role, you will help build scalable data infrastructure for autonomous driving evaluation and training. You will work with cross-functional teams to design pipelines, storage, dashboards, and monitoring that support ML-first systems. You’ll influence data quality and tooling across perception, behavior, and mapping domains, enabling robust evaluation and deployment of the Nuro Driver. This is a hands-on, impact-focused opportunity at a company advancing scalable autonomous mobility. Compensation / Benefitsbase pay within disclosed rangeannual performance bonusequitycompetitive benefits package ResponsibilitiesDesign and develop large-scale batch and streaming data pipelines for evaluation use casesCreate a storage system to handle diverse evaluation metrics and volumesDevelop intuitive dashboards and reports to compare ML component and system performanceMaintain continuous testing and monitoring to ensure data integrity and pipeline resilienceDevelop data mining tools using applied ML for data discovery in Autonomy (Perception, Behavior, Mapping)Develop data annotation tools to support labeling workforce and high-fidelity labelsScale annotation labels with state-of-the-art ML techniques Key requirementsBS, MS, or PhD in a related field with 1+ years of relevant experienceStrong proficiency in Python or similar languagesExperience with large-scale data and building scalable, reliable data pipelinesWillingness to dive into implementation and enforce technical standardsBachelor's degree in Computer Science, Electrical Engineering, or related fieldproblem solvingcollaboration with cross-functional teamsstrong analytical thinkingPythonC++ (bonus)GCP / GCS / BigQuery (bonus)