# Research Engineer - Midtraining — Periodic Labs > Source: > Published: 2026-08-11 21:57:06+00:00 # Research Engineer - Midtraining - Salary - $250k–350k/yr - Location - Menlo Park, CA - Work type - On-site - Posted - today [ Apply on company site (opens in new tab) ](https://jobs.ashbyhq.com/periodic-labs/d3be5ecc-c4d3-4c9e-9a4d-519ab6147474/application) We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and a drive to push the boundaries of what's scientifically possible. About the Role We're training frontier models to develop deep scientific knowledge and reasoning for scientific discovery. As a Midtraining Research Engineer, you'll take base models and improve their scientific reasoning: curating and generating data, building evals, and running large-scale training experiments. Your work will also lay the groundwork for our pre-training efforts down the line. What You'll 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, working closely with RL researchers, physicists, and chemists. - Develop and apply techniques such as self-distillation and on-policy distillation to improve model capability. - Design and run large-scale training experiments, partnering with supercompute engineers to scale efficiently across thousands of GPUs. - Build tools for yourself and the team to investigate how data choices shape model intelligence. You Will Thrive in This Role If You Have - Experience training LLMs on curated mixes of trillions of tokens. - Experience with mid-training or pre-training at scale — big-lab experience is a strong plus. - 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. - The ability to calculate scaling laws and compute-optimal hyperparameters. - Comfort working across data, evals, and training infrastructure. Especially Strong Candidates May Also 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 on a big training run tracking evals and driving interventions while the run was live, not just as a peripheral contributor. Mechanics - Minimum education: Bachelor's degree or similar experience - Location: Menlo Park, CA (Soon: San Francisco, too) - Compensation: $250,000–$350,000 + equity - Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process.