# Research, Pre-Training Science

**Company:** [Thinking Machines Lab](https://hotfix.jobs/companies/thinking-machines-lab)
**Location:** San Francisco, CA
**Role:** AI Research
**Salary:** $350k – $475k/yr
**Skills:** Python, PyTorch, TensorFlow, JAX, Distributed Training, High-Performance Computing, Machine Learning, Deep Learning, Scaling Laws, Optimization, Curriculum Learning, Data Selection, Active Learning
**Posted:** 2026-05-04

> Conducts research on pre-training methodologies for large AI models, develops new architectures and data strategies, runs large-scale experiments, and publishes findings. Requires strong ML fundamentals, Python proficiency, and experience with deep learning frameworks.

## Job Description

## What You’ll Do
- Research and develop new methodologies for pre-training.
- Work in areas such as scaling, architecture, algorithms, or optimization of large scale training runs depending on your research interest and experience.
- Design data curricula and sampling strategies that improve learning dynamics and model generalization.
- Collaborate with infrastructure and data teams to conduct large-scale experiments efficiently and reproducibly.
- Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia.

## Skills and Qualifications

**Minimum qualifications:**
- Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor.
- Experience with distributed or high-performance computing environments.
- Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales.
- Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
- Clarity in communication, an ability to explain complex technical concepts in writing.

**Preferred qualifications:**
- A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs.
- Prior experience training or analyzing large-scale models, or contributing to pre-training or foundation model research.
- Strong publication record or open-source contributions in representation learning, optimization, scaling laws, or other areas of pre-training.
- Familiarity with curriculum learning, data selection, or active learning techniques.
- Experience designing or maintaining evaluation frameworks for large models.
- Contributions to open datasets, research publications, or data tooling.
- PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience.

## Logistics
**Compensation:** Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.

**Benefits:** Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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