Research Scientist, Data
Join Periodic Labs as a Research Scientist to drive evaluations and data strategy for cutting-edge Scientific AI models.
Posted by employer 1 month ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
AI in the day-to-day
You will work on evaluations and data for AI models, ensuring the right assets are available for model improvement.
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience.
Benefits
Joblaze summary
In this role, the Research Scientist in Data will focus on developing and implementing evaluation strategies and data pipelines to enhance AI models in scientific applications. Key skills include expertise in building large-scale data systems and a strong background in scientific research, particularly in materials science or computational physics. This position is well-suited for individuals with a research-oriented mindset and experience in designing benchmarks for AI systems. Periodic Labs is a rapidly growing company at the intersection of AI and physical sciences, emphasizing innovation and collaboration.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Periodic Labs's career page.
- Periodic Labs has 29 other open roles including Don't See Your Role? Apply Here!, Computational Scientist, Differentiable Physics, Environmental Health and Safety.
- 5136 active AI/ML roles on Joblaze right now.
- 148 active Data Engineering roles on Joblaze right now.
- 135 active reinforcement learning roles on Joblaze right now.
- Salary band is above the typical range for AI/ML roles (median ~$188,000).
- Pays more than 80% of the 2231 salaried AI/ML roles we track (median $180,000). See AI/ML salary trends
Quick facts
- Is the Research Scientist, Data role remote?
- It's hybrid — Periodic Labs expects some on-site time in Menlo Park, CA.
- What's the salary range?
- Periodic Labs lists $250,000–$350,000 for this role.
- Where is the role based?
- Periodic Labs is hiring for this position in Menlo Park, CA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, Data Engineering, Materials Science, computational physics, data processing, reinforcement learning.
- 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 senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Scientist, Data role at Periodic Labs.
From the original posting
About Periodic Labs
The most important scientific discoveries of our time won’t happen in a traditional lab. 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 an insatiable drive to push the boundaries of what’s scientifically possible.
About the Role
You will work on the most important aspect of Scientific AI creation: evaluations and data. This means constructing cutting-edge evaluations based on advanced scientific use cases, sourcing and procuring external datasets, integrating internally generated experimental data into the training stack, constructing training environments for RL. You’ll ensure that the team always has the right assets, in the right shape, to evaluate and improve AI models.
You will work with computational and experimental scientists to translate complex scientific workflows into rigorous evaluations and agentic benchmarks, and partner with pretraining, midtraining, and reinforcement learning researchers to identify the data models needed, then build the datasets, environments, and pipelines to deliver it. Your goal will be to create a tight feedback loop between scientific use cases, model evaluation, and training data.
What You’ll Do
Own the evaluation and data strategy across the training stack, identifying capability gaps and shaping the roadmap with leads of physical science and AI research
Work with domain experts to translate advanced scientific workflows into rigorous evals, benchmarks, and RL environments
Source, evaluate, and procure external datasets across chemistry, physics, materials science, mathematics, simulations, and laboratory instrumentation
Build robust pipelines to ingest, clean, and transform for training large-scale datasets from heterogeneous sources
Build tooling and analysis workflows that help researchers inspect data, understand model failures, and determine which evaluations or datasets to develop next
You Will Thrive in This Role If You Have
Designed evaluations, benchmarks, or RL environments for language models, agents, or scientific AI systems
Built large-scale data pipelines for LLM pretraining, midtraining, post-training, or evaluation
Strong judgment about dataset and evaluation quality, including scientific relevance, coverage, provenance, licensing, and contamination risks
Strong software and data engineering skills, including familiarity with data processing at scale, dataset versioning, lineage tracking
A research-oriented mindset: you form hypotheses about data, run controlled experiments, measure model outcomes, and iterate with rigor
Research experience in areas such as materials science, solid state chemistry, chemistry, computational physics, semiconductors
Mechanics
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $250,000-350,000 + equity
Visa sponsorship: Yes, we sponsor visas.