Develop and train state-of-the-art models that fuse raw Lidar and Camera data.
Build perception systems robust enough to handle dynamic occlusion, particulates, and high-vibration conditions.
Optimize models for inference on embedded hardware, debug system-level issues.

3+ years of experience taking deep learning models from research to real-world production using PyTorch.
Deep understanding of SE(3) transformations, homogeneous coordinates, and intrinsic/extrinsic sensor calibration.
Practical experience with architectures that fuse modalities at the feature level.
SOTA Object Detection experience with modern transformer-based architectures including similar temporal models.
Expert in Python and comfortable reading and writing systems code in C++ or Rust.
Understanding of data alignment in robotics.

Machine Learning Engineer – Perception

Key skills