2027 Stanford Career Fair Full-Time Position
XPeng Motors
- 🇺🇸 United States
- On-site
- 2 weeks ago
- AI
- Machine Learning
2 weeks ago
Not enough detail in this posting to match
- 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.
- Hiring across AI andMachine Learning (e.g., foundation models, pretraining, VLA, VLM, LLM, RL),AI Infrastructure, andSoftware Engineering roles.Â
- 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.
- Hiring acrossAI and Machine Learning (e.g., World Models, Behavior Foundation Models, VLA, RL) andMotion Control roles.
2027 Stanford Career Fair Full-Time Position · XPeng Motors