Staff ML Engineer - Road & Lane Detection
仕事内容
Own the roadmap for Road & Lane Detection within the Model Dev ML org — guiding from concept to production-grade maturity.
Research, design, and train advanced architectures (e.g., multi-camera BEV transformers, LiDAR-vision fusion) to detect and model road structures and lane connectivity.
Lead data strategy for this domain, including data curation, labeling policies, and active learning pipelines to capture long-tail scenarios.
Develop robust metrics and evaluation frameworks for lane and road geometry accuracy, temporal consistency, and cross-domain generalization.
Advance foundational capabilities such as self-supervised pretraining, synthetic-to-real adaptation, and temporal modeling for road understanding.
Drive large-scale experiments, mentor engineers, and stay ahead of the research frontier by evaluating emerging techniques for production-grade perception.
Research, design, and train advanced architectures (e.g., multi-camera BEV transformers, LiDAR-vision fusion) to detect and model road structures and lane connectivity.
Lead data strategy for this domain, including data curation, labeling policies, and active learning pipelines to capture long-tail scenarios.
Develop robust metrics and evaluation frameworks for lane and road geometry accuracy, temporal consistency, and cross-domain generalization.
Advance foundational capabilities such as self-supervised pretraining, synthetic-to-real adaptation, and temporal modeling for road understanding.
Drive large-scale experiments, mentor engineers, and stay ahead of the research frontier by evaluating emerging techniques for production-grade perception.
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