Senior Context Fusion AI Engineer - Autonomous Vehicles
Core
Building a learned 3D/4D world model that fuses navigation, ego-motion, perception, and sensor signals to support L3/L4 autonomous driving.
Role type
Senior IC machine-learning engineer (autonomous vehicle context fusion)
Builds
Production-quality AV systems with unified spatiotemporal world representations
Domain
Autonomous Vehicles / Computer Vision / Robotics
Deliverable
production ML models
Required skills
Multimodal sensor fusion, 3D geometry and coordinate frames, deep learning for 3D perception, Transformer architectures, C++ and Python, PyTorch, CUDA, distributed training, uncertainty estimation, BEV representations, foundation model pre-training and fine-tuning
Preferred skills
Multi-task driving models, VLMs, neural scene representation, 3D reconstruction, occupancy-flow, spatiotemporal world-model methods, NVIDIA GPU optimization (TensorRT)
Technologies
PyTorch, CUDA, NVIDIA GPUs, TensorRT, BEV, Transformers, VLMs
Responsibilities
Design learning-based multimodal sensor-fusion systems; Build architectures reasoning over camera, LiDAR, radar, and vehicle-state inputs; Develop end-to-end models for road graph elements, semantic understanding, and occupancy; Create training and evaluation pipelines for large-scale datasets; Investigate foundation-model approaches for autonomous driving; Develop debugging tools for model failures and distribution shift.
Seniority
Senior, hands-on IC with leadership experience
