Staff ML Engineer - BEV & Multi-Modal Perception
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The role
Lead BEV-based perception model development and define the technical roadmap across detection, segmentation, road topology, and scene understanding.
Design advanced multi-modal architectures that fuse camera, LiDAR, radar, and HD maps into unified 3D representations.
Develop foundational perception models using BEV transformers, voxel-based encoders, or implicit scene representations.
Own large-scale training workflows, including data sampling strategies, augmentation pipelines, distributed training, and hyperparameter optimization.
Improve robustness and generalization for long-tail conditions, and establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer.
Collaborate with calibration, mapping, and fusion teams; mentor ML engineers and advance state-of-the-art through self-supervised learning and large-scale pretraining.
Design advanced multi-modal architectures that fuse camera, LiDAR, radar, and HD maps into unified 3D representations.
Develop foundational perception models using BEV transformers, voxel-based encoders, or implicit scene representations.
Own large-scale training workflows, including data sampling strategies, augmentation pipelines, distributed training, and hyperparameter optimization.
Improve robustness and generalization for long-tail conditions, and establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer.
Collaborate with calibration, mapping, and fusion teams; mentor ML engineers and advance state-of-the-art through self-supervised learning and large-scale pretraining.
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