Jobs at XPeng Motors

Internship opportunities supporting General Intelligence and Robotics Centers. Work may involve foundation models, multimodal pretraining, reinforcement learning, autonomous driving, scalable AI infrastructure, inference systems, robotics, world models, embodied agents, manipulation, locomotion, and whole-body motion control.

Lead full-cycle recruiting for XPENG’s U.S. HR team, primarily supporting Mexico, Brazil, and broader Latin America. Responsibilities include talent mapping, sourcing, screening, interview coordination, offer negotiation, stakeholder advising, pipeline analytics, employer branding, and candidate experience. The role requires strong LATAM market knowledge, cross-cultural collaboration, executive communication, and the ability to manage multiple searches onsite in Silicon Valley. Recruiting expertise in AI, machine learning, autonomous driving, robotics, or software engineering is preferred.

Provides end-user IT and network support, manages hardware and software deployments, maintains Windows, macOS, and Linux systems, and administers network infrastructure. Responsibilities include installing and configuring routers, switches, firewalls, cameras, and phones; troubleshooting network performance and security; maintaining technical documentation; supporting disaster recovery; and collaborating with global IT teams and vendors on network solutions.

Build and manage XPENG’s Brazil HR function from the ground up. Responsibilities include HR policies and workflows, employee lifecycle administration, payroll, benefits, recruiting, performance management, employee relations, labor compliance, and vendor coordination. The role partners with Brazilian employees and leaders, regional HR, China headquarters, legal counsel, and external providers while ensuring compliance with Brazilian labor legislation and supporting scalable people operations.

Develop, evaluate, and deploy reinforcement learning methods for autonomous vehicle planning. Design real-time model architectures, build offline data-driven ML infrastructure, analyze fleet and field-testing data, optimize and deploy planning models, and collaborate with perception, software, and AI teams to deliver production autonomous driving systems.

Research, implement, and evaluate deep-learning methods for legged locomotion and whole-body control in humanoid robots. Develop end-to-end robot motion controllers using reinforcement and imitation learning, design and run experiments to address sim-to-real challenges, and integrate state-of-the-art research.

Intern will design and optimize software to deploy large-scale AI models on production vehicles, profile and improve inference across compute, memory, and I/O, reduce latency and power use on embedded automotive platforms, and deliver production-ready, fleet-scalable performance optimizations.

Lead XPENG Mexico’s public relations and communications strategy, including media relations, influencer partnerships, crisis management, product launches, experiential PR, technology storytelling, executive thought leadership, and agency oversight. Build the company’s reputation as an AI mobility and technology leader while coordinating with Sales, Product, PR, and global headquarters. Manage influencer budgets, measure campaign ROI, and translate complex AI and EV innovations into compelling local narratives.

Lead development and productionization of LLM quantization and deployment pipelines (PTQ, QAT, mixed-precision). Implement robust Python production code, build export/calibration/benchmarking workflows, collaborate across research, field-testing, vehicle software, and training infrastructure teams, and curate evaluation datasets and metrics to validate model accuracy, latency, and numerical consistency for on-vehicle inference.

Lead development and productionization of LLM quantization and deployment pipelines (PTQ, QAT, mixed-precision, INT8/FP4), build robust export/calibration/benchmarking/validation tooling, collaborate with research, field-testing, simulation and vehicle software teams, curate evaluation datasets and metrics, analyze numerical errors and performance trade-offs, and develop orchestration workflows for on-vehicle inference and model sign-off.

Design, build, and operate a production AI engineering platform that connects agents to engineering systems. Build reliable distributed services, automation, agent lifecycle and safe action execution, semantic data layers, and observability. Lead customer onboarding, gather requirements, debug production issues, and drive adoption while establishing evaluation and safety guardrails.

Lead cross-functional programs to build and operate an autonomous-driving training data lake: define roadmap, coordinate data/ML/infrastructure/annotation teams, set KPIs for data quality and pipeline reliability, manage dataset generation/versioning/lineage, identify and resolve technical bottlenecks, and improve engineering and operational processes to deliver high-quality training data at scale.