Research Scientist, Scaling RL

The role

You will study how RL scales with training compute and develop better algorithms. You will take ideas from controlled experiments to large runs.

What you will do

• Design experiments to understand how RL performance scales with compute, model size, data, and reward quality
• Develop better RL algorithms, spanning policy optimization, advantage estimation, exploration, and credit assignment for long-horizon RL tasks
• Build adaptive sampling and curriculum methods that adjust task difficulty, problem selection, and the number of rollouts
• Study bias and stability during RL training
• Improve compute efficiency across training and inference through experiments with hyperparameters

Required qualifications

• Bachelor’s degree or similar experience
• Hands-on experience training LLMs with reinforcement learning
• Strong attention to detail and rigorous approach to answer questions scientifically
• Coming up with small-scale RL setups that transfers to large-scale training runs
• Comfort working across a complex training stack to implement, debug, and test new research ideas

Nice to have

• Early career (final year PhD students) are encouraged to apply

Before you apply

• Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process

About the company

Periodic Labs is an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond.