Research Scientist/Research Engineer, Midtraining

The role

You will improve the scientific reasoning of base models by curating data, building evaluations, and running large-scale training experiments. This work will also lay the groundwork for future pre-training efforts.

What you will do

• Identify, process, and curate novel sources of scientific data for large-scale model training.
• Generate high-quality synthetic data to fill gaps in scientific knowledge and reasoning.
• Build evaluations that correlate with downstream scientific task performance.
• Develop and apply techniques such as self-distillation and on-policy distillation.
• Design and run large-scale training experiments with supercompute engineers.
• Build tools to investigate how data choices shape model intelligence.

Required qualifications

• Bachelor's degree or similar experience
• Experience training LLMs on curated mixes of trillions of tokens
• Experience on a dedicated evals team supporting a large production training run
• Hands-on use of self-distillation, on-policy distillation, or similar methods in a real training pipeline
• Experience with scaling laws and compute-optimal hyperparameters
• Comfort working across data, evals, and training infrastructure

Nice to have

• Experience optimizing throughput and reliability for large-scale distributed training runs
• A background in AI for science or training on specialized domain data (e.g., protein, materials, or other scientific datasets)
• Experience creating evals or synthetic data for non verifiable tasks and tracking performance over live runs

Before you apply

• 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.