2027 Stanford Career Fair Full-Time Position

Santa Clara, CA, United States3w ago

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Key details

llmmachine learningmotion control

About General Intelligence Center:

Technical Highlights

Cutting-Edge Physical AI Technology – Leveraging state-of-the-art techniques—including large-scale foundation model training, simulation-driven physical AI, multimodal pretraining, and reinforcement learning —to deliver an autonomous system that is robust and adaptive in real-world scenarios.
End-to-End Autonomous Driving and Intelligent Cabin – Designed to achieve unmatched safety and intelligence, while redefining industry standards and setting new benchmarks in intelligent mobility.
Large-Scale Training and Inference AI Infrastructure – Scalable and efficient AI infrastructure that enables large foundation model training and supports a high-performance inference engine for real-time autonomous decision-making.

Career Pathways

Hiring across AI and Machine Learning (e.g., foundation models, pretraining, VLA, VLM, LLM, RL), AI Infrastructure, and Software Engineering roles.

About Robotics Center:

Technical Highlights

Robotics Foundation Models – Building world foundation models for whole-body intelligence.
Physical Agents – Building self-evolving embodied agents that can perceive, reason, plan, and act robustly in complex real-world environments.
Manipulation – Advancing loco-manipulation and dexterous manipulation, while tackling key challenges in tactile intelligence and VLA scaling.
Locomotion & Whole-Body Control – Advancing human-like locomotion (e.g., RL controllers) and whole-body control.

Career Pathways

Hiring across AI and Machine Learning (e.g., World Models, Behavior Foundation Models, VLA, RL) and Motion Control roles.

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