Member of Technical Staff (MTS) - Multimodal Foundation Models

Focus

Multimodal Foundation Models · Representation Learning · Method Innovation

We are looking for strong technical builders and researchers who deeply understand foundation models and representation learning beyond simply applying existing frameworks.

Ideal candidates should have:

• Strong experimental rigor
• Solid systems and modeling intuition
• Hands-on engineering ability
• Interest in scalable multimodal AI systems for real-world autonomy

We value people who can bridge research and production, and who care about robustness, scalability, efficiency, and practical deployment in large-scale autonomous driving systems.

Responsibilities

1. Large-Scale Foundation Model Pretraining

• Develop scalable pretraining pipelines for large-scale multimodal driving data
• Design and optimize training strategies for:
• Vision-language-action models
• Video foundation models
• Long-context temporal modeling
• Multimodal representation alignment
• Improve:
• Training stability
• Data efficiency
• Scaling efficiency
• Representation robustness
• Work on distributed training systems and large-scale model optimization using frameworks such as:
• PyTorch Distributed
• DeepSpeed
• Megatron-LM

2. Representation Learning &am