Data Engineer/Senior Data Engineer

Join our team as a Data Engineer/Senior Data Engineer, where you will play a crucial role in quantifying and analyzing driving performance metrics for our virtual driver. You will work primarily in Python and be responsible for building scalable data processing pipelines, conducting in-depth analysis of road-test and simulation data, and developing geospatial analytics. Additionally, you will contribute to release management and build AI workflows for issue triage. This position offers unlimited PTO, flexible working arrangements, health benefits, equity options, professional development opportunities, and daily catered lunches.

• Définir et calculer les métriques de performance de conduite, y compris la sécurité, le confort, le progrès, les interventions et la conformité, et construire des pipelines évolutifs pour les évaluer de manière cohérente.
• Analyser en profondeur les données de tests routiers et de simulation pour identifier les tendances, les régressions et les anomalies dans le comportement d'autonomie, et les transformer en conclusions claires.
• Construire les fondations de données et les outils pour la gestion des versions, y compris les comparaisons version par version, les critères de préparation et de contrôle, et les preuves traçables soutenant les décisions de publication.

• You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn
• We are open to candidates at either the Engineer or Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact
• Experience building LLM-powered or agentic workflows for data analysis, evaluation, or automation
• Proficiency in Python, with experience building scalable data processing systems or evaluation frameworks
• Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end
• Experience developing metrics and analyzing large-scale time-series, event, or geospatial data, including principled metric definitions, validation, and error analysis
• BS, MS, or PhD in Computer Science, engineering, or a related technical field, or equivalent practical experience
• Ability to solve open-ended technical challenges and communicate findings clearly to engineering and program stakeholders
• Experience with distributed data processing such as Apache Spark, and workflow orchestration such as Airflow or Argo Workflows
• Experience with geospatial data and tooling, such as GIS formats, map matching, spatial indexing and joins, PostGIS, GeoPandas, or map-based visualization libraries
• Familiarity with LLM agent frameworks (e.g., LangChain, LangGraph, or similar) and prompt/tool-orchestration patterns
• Experience with release engineering, quality gating, or automated regression detection
• Experience with autonomous vehicles, robotics, or other safety-critical systems
• Experience building dashboards or analytics interfaces that expose metrics to users