Research Scientist/Research Engineer, Midtraining
Join Periodic Labs as a Midtraining Research Engineer to enhance scientific reasoning in AI models for groundbreaking discoveries.
Posted by employer 1 day ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
- Identify, process, and curate novel sources of scientific data
- Generate high-quality synthetic data
- Build evaluations that correlate with downstream scientific task performance
- Develop and apply techniques to improve model capability
- Design and run large-scale training experiments
Must have
- Experience training LLMs on curated mixes of trillions of tokens
- Hands-on use of self-distillation, on-policy distillation, or similar methods
- 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
- Experience creating evals or synthetic data for non verifiable tasks
AI in the day-to-day
We're training frontier models to develop deep scientific knowledge and reasoning for scientific discovery.
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience, work arrangement.
Benefits
Joblaze summary
In the role of Midtraining Research Engineer at Periodic Labs, the individual will focus on enhancing scientific reasoning in AI models by curating data, generating synthetic datasets, and conducting large-scale training experiments. Key skills include experience with large language models, self-distillation techniques, and a solid understanding of training infrastructure. This position is well-suited for candidates with a background in AI for science and those familiar with optimizing distributed training processes. The company is rapidly growing and operates at the forefront of AI and physical sciences.
Joblaze insights
- Listed yesterday — first seen on Joblaze October 1, 2026. Last confirmed on Periodic Labs's careers page October 1, 2026.
- Salary band is above the typical range for AI/ML roles (median ~$190,000).
- Starts above 93% of 81 comparable mid ai/ml roles in United States that list AI/ML we track (median $152,000 across 37 companies). See AI/ML salary trends
- AI/ML appears in 50.9% of 450 comparable mid ai/ml roles in United States; self-distillation appears in 0.2% of 450 comparable mid ai/ml roles in United States.
Quick facts
- What's the salary range?
- Periodic Labs lists $250,000–$350,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, GPU, Large Language Models, on-policy distillation, self-distillation, supercomputing.
- Does Periodic Labs sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Periodic Labs targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Scientist/Research Engineer, Midtraining role at Periodic Labs.
From the original posting
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.
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.
Standard company text repeated across Periodic Labs's postings is omitted here.