Senior Machine Learning Engineer, Data for Embodied AI
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Die Stelle
Design, scale, and optimize large-scale multimodal data pipelines for embodied AI.
Own the full data lifecycle: ingestion, preprocessing, filtering, annotation, and storage for video, LiDAR, and telemetry.
Develop metrics and experiments to quantify data quality and its impact on model performance.
Collaborate with ML researchers and platform engineers to integrate datasets into high-throughput training workflows.
Build internal tooling for auditing, visualization, and reproducibility (versioning, lineage, dashboards).
Establish data governance, safety, privacy, and long-term maintainability across the data lifecycle in a fast-paced setting.
Own the full data lifecycle: ingestion, preprocessing, filtering, annotation, and storage for video, LiDAR, and telemetry.
Develop metrics and experiments to quantify data quality and its impact on model performance.
Collaborate with ML researchers and platform engineers to integrate datasets into high-throughput training workflows.
Build internal tooling for auditing, visualization, and reproducibility (versioning, lineage, dashboards).
Establish data governance, safety, privacy, and long-term maintainability across the data lifecycle in a fast-paced setting.
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