Description
Torc, now part of the Daimler family, is seeking an experienced engineer to join their Auto Tagger team. This role involves architecting and optimizing distributed data pipelines to extract and catalog safety-critical driving events from massive multi-sensor logs. The successful candidate will develop and tune advanced event tagging algorithms, utilizing both heuristic-based approaches and machine learning, particularly exploring Vision-Language Models or semantic vector search. They will also focus on standardized data structuring using the Pegasus layer standard, ensuring semantic consistency and metadata integrity. Additionally, the role includes managing data ingestion into the observations database for high-speed querying and retrieval, integrating with ML training and system validation. Cross-functional alignment with perception, simulation, and systems engineering teams is crucial to define interesting scenarios and maintain a continuous data loop. Mentorship and fostering a culture of technical excellence are also significant aspects of this leadership-oriented role.
