XPENG

Lead a small interdisciplinary team advancing frontier robotics research from technical vision and roadmap through prototypes and real-world validation. The role combines hands-on work across AI algorithms, simulation, robot systems, and experimentation.

XPENG is hiring a Senior Machine Learning Engineer to build large-scale ML infrastructure for training and serving foundation models powering autonomous driving, robotics, and other physical AI applications. The role focuses on distributed training, inference acceleration, and massive-scale data pipelines.

Staff Machine Learning Engineer developing reinforcement-learning planning systems for autonomous vehicles. The role combines ML research, software engineering, real-time model optimization, and deployment using large-scale fleet data.

Build and productionize quantized VLA and LLM inference systems for XPENG’s next-generation Turing AI chip and autonomous-driving platforms. This staff-level role combines model optimization, deployment pipelines, numerical validation, and cross-functional performance sign-off.

Develop and productionize LLM quantization and VLA inference systems for deployment on XPENG’s Turing AI chip and autonomous vehicles. The role combines model optimization, benchmarking, deployment pipelines, and cross-functional performance sign-off.

Build predictive world models that simulate how driving and robotics scenes evolve, using generative modeling and large-scale multimodal deep learning. You will advance autonomous-driving and robotics policy training through world-model research, evaluation, and implementation.

Join the General Intelligence Center as a Campus Recruiting Intern, focusing on cutting-edge AI and machine learning technologies.

Build the internal AI engineering platform that connects software agents to engineering systems, workflows, and operational actions. This role combines robust backend platform engineering with agentic systems, automation, customer onboarding, and safe execution.