About the role

What you’ll do

• Own the path from raw multimodal vehicle data to versioned, model-ready autonomous-driving datasets
• Lead dataset architecture, ingestion, storage, query, curation, quality monitoring, labeling automation, and training readiness
• Coordinate technical requirements across partner teams
• Design automated data validation and observability for ML training and evaluation needs
• Optimize distributed ML data loading, caching, sampling, and preprocessing
• Prepare sequential and trajectory datasets for imitation learning and reinforcement learning

What you’ll need

• 8+ years of experience in applied machine learning or deep learning
• 4+ years of experience in reinforcement learning, computer vision, or AD/ADAS systems
• Deep production experience with Parquet and/or Lance, including dataset migration, indexing, compaction, and schema evolution
• Experience with large-scale multimodal autonomous-driving data from cameras, LiDAR, radar, maps, and other sensors
• Strong Python and SQL skills with production software-engineering practices
• Experience building distributed data pipelines using Ray, Spark, Beam, Dask, Airflow, Dagster, or comparable systems

Original job description