Staff VLA Engineer

About Us

We are looking for the best About Us 42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.

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