Senior Staff Research Engineer – Reinforcement Learning For Ai Agents

XPENG Inc.

Santa Clara, CA, United States
Base: $244,140 - $413,160; bonus/equity: not speci...
On-site
Reinforcement learning algorithms implementation
Policy optimization for long-horizon reasoning
Python programming with pytorch or jax
This role sits at the intersection of reinforcement learning, large language models, and real-world autonomous systems to build learning systems that power continuously improving agents

Job Summary

  • This role sits at the intersection of reinforcement learning, large language models, and real-world autonomous systems to build learning systems that power continuously improving agents.
  • Key responsibilities include developing RL methods for LLM-driven decision systems, optimizing policies for long-horizon planning, and creating evaluation benchmarks for agent capabilities.
  • The company offers a competitive compensation package ranging from $244,140 to $413,160 along with opportunities to impact the transportation revolution through advanced autonomous driving technologies.

Matching Summary

This role sits at the intersection of reinforcement learning, large language models, and real-world autonomous systems to build learning systems that power continuously improving agents.

Salary

Base: $244,140 - $413,160; Bonus/Equity: Not specified; Benefits: Snacks, lunches, fun activities, competitive compensation package

Skills & Requirements

Must-have

  • Reinforcement learning algorithms implementation
  • Policy optimization for long-horizon reasoning
  • Python programming with PyTorch or JAX
  • ML training systems infrastructure development
  • Experience with PPO or Actor-Critic methods

Nice-to-have

  • RLHF or preference learning experience
  • LLM agents or tool-using AI systems
  • Multi-agent systems and simulation environments
  • Publications in NeurIPS, ICML, ICLR, or ACL
  • Real-world and simulation data integration loops

Key Requirements

  • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or related field
  • Strong background in reinforcement learning or machine learning
  • Experience implementing RL algorithms such as PPO, Actor-Critic, or policy gradient methods

Work Rights

Not specified

Tailored Resume

Cover Letter