Staff VLA Engineer

As a Staff VLA Engineer you'll contribute to next-generation autonomous driving intelligence research, working alongside the team to push past current VLA capabilities. You'll bring hands-on expertise in foundation models, multimodal learning, world models, or autonomous systems, and help turn research ideas into real technical progress.

Responsibilities

Contribute to Next-Generation VLA Architectures

• Research and prototype next-generation Vision-Language-Action architectures.
• Explore scalable multimodal foundation models for autonomous driving.
• Help develop architectures with improved generalization, reasoning, and long-horizon decision making.
• Support work on large driving models that unify perception, planning, and action generation.

Support World Model & Driving Reasoning Research

• Build and experiment with world-model-based approaches for predictive driving intelligence.
• Work on future-state prediction, behavior forecasting, and counterfactual simulation.
• Contribute to long-horizon planning and reasoning research for autonomous driving.
• Help build models that understand complex traffic interactions and latent agent intentions.

Explore Agentic Driving Systems

• Research goal-driven autonomous driving agents.
• Help develop architectures that integrate reasoning, planning, memory, and action.
• Investigate driving agents capable of adaptive decision making in open-world environments.
• Contribute ideas toward future driving-agent architectures as successors to current VLA systems.

Qualifications

• MS or PhD in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field (or equivalent practical experience).
• Strong hands-on experience with deep learning frameworks (e.g., PyTorch, JAX).
• Solid understanding of foundation models, multimodal learning, or transformer-based architectures.
• Experience training or fine-tuning large-scale models (vision, language, or multimodal).
• Strong software engineering skills and experience working with large-scale data pipelines.
• Ability to read, implement, and extend ideas from recent AI research papers.
• Excellent collaboration and communication skills, comfortable working across distributed, cross-functional, and cross-cultural teams (Silicon Valley + HQ Korea).

Preferred Qualifications

• Research experience in autonomous driving, robotics, or embodied AI (e.g., perception, planning, control, or end-to-end driving models).
• Experience with world models, model-based reinforcement learning, or predictive/generative simulation.
• Familiarity with Vision-Language-Action (VLA) models or agentic AI architectures (reasoning, planning, memory, tool use).
• Publications at top-tier AI/ML/robotics venues (e.g., NeurIPS, ICML, ICLR, CVPR, CoRL, RSS).
• Experience with large-scale distributed training and model optimization.
• Prior experience contributing research to production systems or bringing prototypes to deployment.
• Familiarity with simulation environments for autonomous driving (e.g., CARLA, nuPlan, Waymo Open Dataset).

Compensation

• $189,000 to $311,220