# Research Scientist/Research Engineer, Midtraining

**Company:** [Periodic Labs](https://zerogtalent.com/ai-companies/periodic-labs)
**Location:** Menlo Park, CA
**Work mode:** On-site
**Seniority:** Mid
**Employment type:** Full Time
**Salary:** USD 250K–350K/yr
**Category:** Engineering
**Department:** Engineering
**Listed:** 2026-09-30

[View and apply on Zero G Talent](https://zerogtalent.com/ai-jobs/periodic-labs/research-scientist-research-engineer-midtraining-168dbf20-2230-49a0-9f00-f2ff58dad5c8)

## What you'll do

- Curate novel scientific data sources for large-scale model training
- Generate high-quality synthetic data for scientific reasoning gaps
- Build evaluations correlating with downstream scientific task performance
- Develop and apply self-distillation/on-policy distillation techniques
- Design and run large-scale training experiments across thousands of GPUs

## What you need

- Experience training LLMs on trillions of tokens
- Experience on dedicated evals team for large training run
- Hands-on self-distillation/on-policy distillation in training pipeline
- Experience with scaling laws and compute-optimal hyperparameters
- Comfort across data, evals, and training infrastructure

## Job description

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 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.
    

### **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 creating evals or synthetic data for non verifiable tasks and tracking performance over live runs.
    

### **Mechanics**

-   **Minimum education:** Bachelor's degree or similar experience
    
-   **Location:** Menlo Park, CA
    
-   **Compensation:** $250,000–$350,000 + equity
    
-   **Visa sponsorship:** Yes, we sponsor visas and will do everything we can to assist in this process.

## Other open roles at Periodic Labs

- [Process Safety Engineer](https://zerogtalent.com/ai-jobs/periodic-labs/process-safety-engineer-1d57d49b-e538-4d9a-86d3-6be17339016f) — Menlo Park, CA
- [Controller](https://zerogtalent.com/ai-jobs/periodic-labs/controller-6c188bbb-1f81-4145-aac3-28cb0e47e3cc) — Menlo Park, CA
- [Research Scientist, Scaling RL](https://zerogtalent.com/ai-jobs/periodic-labs/research-scientist-scaling-rl-20b122c9-b8ec-4fb0-aaf4-9b45902affe0) — Menlo Park, CA; Montreal, Canada
- [XRD Facility Manager](https://zerogtalent.com/ai-jobs/periodic-labs/xrd-facility-manager-e82a30cb-ad71-402f-b1c2-1b762fc50bfe) — Menlo Park, CA
- [Computational Scientist, Differentiable Physics](https://zerogtalent.com/ai-jobs/periodic-labs/computational-scientist-differential-physics-ccdb34b1-b67c-4dbf-8acb-fe786f2ab38b) — Menlo Park, CA

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