Staff, ML Engineer - Road & Lane Detection

Own the Road & Lane Detection model roadmap from concept to production-grade maturity, ensuring robust perception of road geometry and lane connectivity.

Design, train, and validate advanced architectures (e.g., BEV transformers, LiDAR-vision fusion) for accurate road and lane semantics from multi-modal data.

Define data strategy, labeling policies, and active learning pipelines to capture challenging long-tail scenarios.

Develop robust metrics and evaluation frameworks for lane/road accuracy, temporal consistency, and cross-domain generalization.

Advance foundational capabilities such as self-supervised pretraining, synthetic-to-real adaptation, and temporal modeling.

Lead and mentor engineers, collaborate across perception teams, and drive scalable experimentation and model improvements.