Model Engineer, Post-Training & RL
xAI, Palo Alto, CA
The role
You will work on the most critical post-training and reinforcement learning challenges at any given time — including reward modeling, preference optimization (RLHF/DPO), and RL for improving reasoning, truthfulness, and real-world capabilities.
What you will do
- Design and run rigorous experiments that turn research ideas into measurable gains in model capability
- Improve model recipes through data quality, deduplication, and mixture experiments
- Define what makes RL data and rewards good, including grader design and preventing reward hacking