Senior Staff Research Engineer – Reinforcement Learning for AI Agents

XPENG • Santa Clara, CA

2d

About The Position

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
We are looking for exceptional Research Engineers / Scientists to design learning systems that allow agents to plan over long horizons, learn effective strategies, and improve through experience.
This role sits at the intersection of reinforcement learning, large language models, and real-world autonomous systems. Autonomous systems must operate reliably in complex, dynamic environments. We believe the next generation of autonomy will involve learning agents that continuously improve through interaction, feedback, and large-scale data. You will help build the learning systems that power these agents.

Requirements

• MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field.
• Strong background in reinforcement learning or machine learning.
• Experience implementing RL algorithms such as PPO, Actor-Critic, or policy gradient methods.
• Strong programming skills in Python with PyTorch or JAX.
• Experience building ML training systems or infrastructure.

Nice To Haves

• Experience with RLHF or preference learning.
• Experience with LLM agents or tool-using AI systems.
• Multi-agent systems or long-horizon planning.
• Simulation environments for RL.
• Publications in NeurIPS, ICML, ICLR, ACL, or related venues.

Responsibilities

• Reinforcement learning methods for LLM-driven agents and decision systems.
• Policy optimization for long-horizon reasoning and planning.
• Learning from human or AI feedback (RLHF / RLAIF).
• Agent training pipelines built on top of our agent infrastructure platform.
• Evaluation and benchmarking systems for agent capabilities.
• Learning loops that integrate real-world and simulation data.
• Contribute to AI systems that continuously improve after deployment.

Benefits

• A fun, supportive and engaging environment.
• Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving.
• Opportunity to work on cutting edge technologies with the top talent in the field.
• Competitive compensation package.
• Snacks, lunches and fun activities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 501-1,000 employees