XPeng Motors

You'll architect **PB-scale data pipelines** for autonomous driving and foundation models. Your impact enables self-driving systems to learn from massive datasets. This role bridges raw vehicle logs and model-ready tokens.

You'll design and deploy **advanced manipulation algorithms** for humanoid robot dexterous hands using teleoperation, force control, and reinforcement learning. You'll develop high-fidelity simulation environments and **tackle core technical challenges** in robot task execution. This role offers the chance to work on cutting-edge robotics with top talent in the field.

You'll architect and build scalable data pipelines for PB-scale autonomy and multi-modal LLM data, evolving our lakehouse architecture with Apache Iceberg and Lance. Your work will directly determine how our self-driving systems learn from massive datasets. This role sits at the intersection of **Autonomous Driving** and **Foundation Models**.

You'll **build end-to-end data pipelines** for autonomous driving, handling petabyte-scale sensor data from upload to model training. Your work directly **accelerates algorithm iteration** through reliable, observable, and cost-effective infrastructure. Join a team at the forefront of **intelligent mobility and AI innovation**.

You'll **design and optimize software** for deploying large-scale AI models in production vehicles at XPENG, a leader in smart EV and autonomous driving technology. You'll profile and improve inference performance across compute, memory, and I/O systems, reducing latency and power efficiency on embedded automotive platforms. This role offers impact on **real-world autonomous driving** with top talent.

You'll architect the transition to intelligent, zero-shot decision-making for L4 autonomous vehicles using VLA and world models. Your core impact is leading end-to-end VLA architecture design and scaling data strategies for global generalization. This role offers the chance to work with top talent on cutting-edge autonomous driving technology.

You'll build the end-to-end **data pipeline for autonomous driving**, from onboard upload to model training. Your work will directly enable **petabyte-scale sensor data processing** and accelerate algorithm iteration. This role sits at the core of AI infrastructure for a leading smart EV company.

You'll lead **applied AI development** at XPENG, building production-grade systems using LLMs, RAG, and agentic workflows. You'll define architecture and reusable patterns to enable AI adoption across teams, setting a high bar for reliability and evaluation. This role offers the chance to shape the future of intelligent mobility.

You'll build **internal AI infrastructure platforms** for autonomous driving and AI systems. You'll work on **LLM orchestration, multi-agent coordination, and automated workflow systems** to enhance developer productivity. This role offers hands-on experience with **AI-native tooling and scalable infrastructure** at the frontier of enterprise AI.

You'll build the data foundation for an **LLM-powered agent** that helps Machine Learning Engineers collect and analyze **experiment context** for autonomous driving AI. Your work will directly enable **smarter insights** across ongoing model development, accelerating XPENG's intelligent mobility mission.

You'll support optimization and deployment of **multimodal models** onto vehicle-grade compute platforms. You'll contribute to making **autonomous driving systems** production-ready. This role is ideal for those excited about **edge inference** and real-world AI applications.

You'll fine-tune large language models for **humanoid robots** and **autonomous driving** use cases. Your work will enable efficient LLM deployment on edge devices, directly impacting the future of intelligent mobility.

You'll develop and maintain machine learning models for **humanoid robots** in a **lean, cross-functional team**. Your work will directly impact every shipped product from **foundation model optimization** to synthetic data generation.

You'll design and train **large-scale multi-modal models** for XPENG's **Vision-Language-Action Foundation Model**, the core brain powering end-to-end autonomous driving. Your work will directly shape L3/L4 driving intelligence by scaling pretraining across thousands of GPUs.

You'll lead the modeling and algorithmic development of XPENG's next-generation **Vision-Language-Action Foundation Model**, the core brain powering end-to-end autonomous driving. Your work will directly shape **L3/L4 autonomous driving products** by designing large-scale multi-modal architectures and training strategies.

You'll **optimize transformer-based LLMs** for low-latency, high-throughput inference and **contribute to ML infrastructure** for training large foundation models. Your work will directly **enable next-generation E2E autonomous driving solutions** at XPENG.

You will develop and optimize **multi-modal models** and **computer vision systems** for autonomous driving applications. Collaborate with cross-functional teams to deploy production-ready solutions with low latency and high throughput. This role offers the chance to work on cutting-edge AI technologies reshaping transportation.

You'll lead the **architecture and technological evolution** of the next-generation synthetic data and Digital World generation system at **XPENG**, supporting autonomous driving and robotics. Your core impact will be building high-fidelity virtual worlds and closed-loop simulation. This role offers the opportunity to shape cutting-edge AI and autonomous systems.

You'll **optimize transformer-based LLMs** for a **leading autonomous driving company**, enabling next-generation E2E solutions. You'll push the boundary of state-of-art machine learning models on a high-impact team.

You'll design and implement modules within XPENG's **autonomous software stack**, focusing on AI 2.0 data close loop software. You'll analyze system performance, propose optimizations, and debug bottlenecks. This role offers the chance to work on **cutting-edge smart mobility technologies** for a leading AI-driven automotive company.

You'll define the architecture of a **vehicle-cloud integrated data closed-loop** system supporting **weekly model iteration** and cross-regional expansion. Your work will directly enable autonomous driving and embodied intelligence advancements at a leading smart EV company.

You'll develop **machine learning models** and **training pipelines** for humanoid robots at a leading smart tech company. You'll work on efficient foundation models for **local deployment** in robots. This role offers impact on cutting-edge robotics and transportation.

You'll join XPENG's US robotics team, developing **control and learning-based algorithms** for humanoid robot locomotion and whole-body motion. Your core impact will be contributing to **sim-to-real deployment** and helping coordinate a small team. This role stands out with the chance to work on **cutting-edge humanoid robots** from research to product.

You'll drive the modeling and algorithmic development of XPENG's next-generation **Vision-Language-Action Foundation Model** for autonomous driving. Your work will directly shape the intelligence enabling **L3/L4 autonomous driving products**. You'll collaborate with world-class researchers and engineers in a **research-driven environment** with access to massive real-world data and industry-scale compute.

You'll plan and coordinate **software stack delivery** for XPENG vehicles and drive **KPI-driven development processes** across teams. Your work ensures reliable mass-market **autonomous vehicle solutions**.

You'll design learning systems for AI agents at the intersection of **reinforcement learning**, **large language models**, and **autonomous systems**. You'll build agent training pipelines and feedback loops that enable continuous improvement after deployment.