Senior Radar Perception Engineer, Obstacle Foundation Models - Autonomous Vehicles
Core
Design and productize NVIDIA's next-generation autonomous driving perception stack, focusing on 3D radar and multi-modal obstacle perception pipelines using transformer-based foundation models and multi-sensor fusion.
Role type
Senior IC machine-learning engineer (radar perception)
Builds
Radar-based 3D obstacle perception models and multi-sensor fusion pipelines for L2-L4 autonomous driving
Domain
Autonomous vehicles, radar signal processing, deep learning
Deliverable
production ML models
Required skills
Deep learning (DNN, transformers), radar signal processing, multi-sensor fusion, Python, C++, CUDA, embedded optimization, data strategy, model evaluation
Preferred skills
Radar physics (FMCW, beamforming, CFAR, micro-Doppler), GPU acceleration (custom kernels), academic publication record, experience with BEV networks
Technologies
PyTorch, CUDA, Transformers, BEV networks, LoRA
Responsibilities
Develop technical architecture and roadmap for radar perception; conduct applied research on deep learning models for radar point clouds; design and implement 3D perception models and multi-sensor fusion; drive sensor evaluation and layout optimization; build efficient production-grade deep learning models; define and maintain KPI frameworks for performance analysis; contribute to data strategy and auto-labeling workflows; collaborate with cross-functional teams for productization
Seniority
Senior, hands-on IC
