Machine Learning Engineer: Perception

About this role

Responsibilities

• Design Early Fusion Architectures: Develop and train state-of-the-art models (e.g., BEV-based transformers) that fuse raw Lidar and Camera data to solve for object detection and semantic segmentation.
• Tackle 'Messy' Physics: Build perception systems robust enough to handle dynamic occlusion (seeing the robot’s own arm/bucket), particulates (dust, snow, rain), and high-vibration conditions.
• Deploy to the Edge: Optimize models for inference on embedded hardware. You will debug system-level issues, such as sensor calibration drift and latency bottlenecks.
• Collaborating with other teams to create state-of-the-art representations for downstream use cases.
• Production ML Experience: 3+ years of experience taking deep learning models from research to real-world production using PyTorch, Tensorflow, or JAX.