27 days ago
Santa Clara, CA, USASenior / Staff+
Base Salary
$244k - $413k/yr
Responsibilities
- Develop reinforcement learning methods for LLM-driven agents and decision systems.
- Optimize policies for long-horizon reasoning and planning.
- Implement learning from human or AI feedback (RLHF/RLAIF).
- Build agent training pipelines on the agent infrastructure platform.
- Create evaluation and benchmarking systems for agent capabilities.
- Integrate real-world and simulation data into learning loops.
- Contribute to AI systems that continuously improve after deployment.
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.
Benefits
- A fun, supportive and engaging environment.
- Opportunity to make significant impact on transportation revolution.
- Work on cutting edge technologies with top talent in the field.
- Competitive compensation package.
- Snacks, lunches, and fun activities.