Senior Applied AI Engineer - Multimodal Transformers
Core
Designing and developing multimodal transformer architectures that fuse camera, LiDAR, and radar data for autonomous ground transportation.
Role type
Senior Applied AI Engineer (Multimodal Transformers)
Builds
AI-powered autonomy stack for commercial trucking and public sector defense applications
Domain
Autonomous vehicles / Computer Vision / Deep Learning
Deliverable
production ML models
Required skills
transformer architectures, multimodal fusion, cross-attention mechanisms, token fusion, scalable distributed training, mixed-precision optimization, Python, PyTorch, TensorFlow
Preferred skills
self-supervised learning, contrastive pretraining, real-time inference optimization
Technologies
PyTorch, TensorFlow, Python
Responsibilities
Design and develop multimodal transformer architectures; Research and implement cross-modal attention mechanisms; Build scalable training pipelines for large-scale models; Explore self-supervised and contrastive pretraining objectives; Optimize transformer models for real-time inference
Seniority
Senior, hands-on IC