Senior Machine Learning Engineer, Multimodal Perception

Perception-focused MLE role dedicated to multi-modal sensor fusion, multi-task deep learning architectures for vehicle semantics and signal detection, dynamic high-resolution vision backbones, and large-scale automated data engines.

In this hybrid role, you will report to the Technical Lead Manager of the Special Vehicle Compliance team.

Architect, train, and optimize multi-task deep learning models (PyTorch / JAX) across multi-modal sensor streams.

Build automated data mining pipelines, active learning loops, hard-example curation, and auto-labeling systems.

Develop high-resolution vision architectures and spatial-temporal transformer backbones.

Leverage multimodal foundation models for automated data curation, synthetic edge-case generation, and failure triage.

Profile and optimize models for efficient onboard accelerator inference.

2–5+ years training and deploying production vision or multi-modal deep learning models.

Experience with multi-modal sensor fusion (Camera + LiDAR + Audio), multi-task learning (MTL), transformer architectures, and PyTorch / JAX.

Experience building large-scale data curation pipelines, active learning loops, and auto-labeling systems.