Staff ML Engineer - BEV
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The role
Lead BEV-based perception models across tasks such as detection, segmentation, road topology, and scene understanding.
Design advanced multi-modal architectures that fuse camera, LiDAR, radar, and HD maps into unified spatial representations.
Own large-scale training workflows—from data sampling and augmentation to distributed training and hyperparameter optimization.
Advance model robustness and generalization under long-tail conditions, including low visibility and occlusions.
Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer; collaborate with calibration, mapping, and fusion teams.
Mentor ML engineers, promote experimentation and code quality, and stay at the forefront of ML research (self-supervised learning, large-scale pretraining, foundation models for 3D perception).
Design advanced multi-modal architectures that fuse camera, LiDAR, radar, and HD maps into unified spatial representations.
Own large-scale training workflows—from data sampling and augmentation to distributed training and hyperparameter optimization.
Advance model robustness and generalization under long-tail conditions, including low visibility and occlusions.
Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer; collaborate with calibration, mapping, and fusion teams.
Mentor ML engineers, promote experimentation and code quality, and stay at the forefront of ML research (self-supervised learning, large-scale pretraining, foundation models for 3D perception).
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