The Auto Tagger team is responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios
Job Summary
The Auto Tagger team is responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios.
This role involves architecting and optimizing distributed data pipelines to automatically extract safety-critical and long-tail driving events from massive sensor logs.
Candidates will develop advanced event tagging algorithms using heuristic-based and ML-assisted approaches, including exploring Vision-Language Models.
Matching Summary
The Auto Tagger team is responsible for translating petabytes of raw, multi-modal vehicle data into a highly curated library of critical driving scenarios.
Skills & Requirements
Must-have
Distributed data pipeline architecture
Multi-sensor log processing
Heuristic and ML algorithm development
Vision-Language Models or semantic vector search
Pegasus logical layer standard
Observations database management
Nice-to-have
Mentoring less-experienced engineers
Cross-functional collaboration skills
Culture of technical excellence
Continuous data loop operationalization
Key Requirements
Senior level experience in Machine Learning Engineering
Experience with large-scale data processing systems
Background in autonomous vehicle perception or simulation