Staff VLA Engineer

Sunnyvale, United Statesfull timeOn Site

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senior

$189k–$311k

H1B: no

42dot The Staff VLA Engineer at 42dot researches and prototypes next-generation Vision-Language-Action architectures for autonomous driving. The role involves developing scalable multimodal foundation models and supporting world model and driving reasoning research.

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.

Qualification

MS or PhD in Computer ScienceAbility to readExperience with world modelsInterview Process

Required

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

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).
Interview Process