Senior/Staff Machine Learning Engineer, Perception
Core
Build perception systems that give autonomous heavy machinery human-like awareness in rugged, unstructured environments by processing camera and LiDAR data into robust 3D scene understanding.
Role type
Senior/Staff Machine Learning Engineer (Perception)
Builds
Real-time perception models, multi-modal fusion systems, auto-labeling pipelines, and data/evaluation pipelines for autonomous fleet services.
Domain
Agriculture and turf management; Autonomous Physical AI; Computer Vision and Sensor Fusion.
Deliverable
production ML models
Required skills
Computer vision (detection, segmentation, depth, BEV, occupancy), multi-sensor fusion (camera, LiDAR, radar), model distillation and fine-tuning, Python, PyTorch/TensorFlow/OpenCV, real-time system optimization, dataset curation and labeling pipelines, performance metric analysis (mAP, IoU, latency).
Preferred skills
Architecting multi-sensor ML systems from scratch, building auto-labeling/data-engine flywheels, compute-constrained deployment (TensorRT, quantization, CUDA), predictive world models, VLA/WAM paradigms, top-tier publications (CVPR, ICRA, CoRL, RSS).
Technologies
PyTorch, TensorFlow, OpenCV, TensorRT, CUDA, BEV, LiDAR, GNSS.
Responsibilities
Develop real-time perception models for open-world obstacle and terrain understanding; Build multi-modal fusion combining camera and LiDAR into unified 3D/BEV representation; Optimize models for low-latency inference on resource-constrained hardware; Design auto-labeling pipelines leveraging foundation models and teacher-student distillation; Design data and evaluation pipelines to curate datasets and surface failures; Analyze performance metrics and iterate on algorithms to improve accuracy and efficiency.
Seniority
Senior/Staff, hands-on IC with ownership
