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# Research, Pre-Training Data

- **Company:** Thinking Machines Lab Inc.
- **Location:** San Francisco, CA, United States
- **Salary:** $350,000
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Information Engineering, Data Files, Data Transformation, Data Systems, Software Debugging, Experimental Data, Python (Programming Language), Machine Learning, Tensorflow, Data Processing, Pytorch, Deep Learning, Information Technology, Software Coding
- **Published:** November 12, 2026
- **Apply:** https://www.careerbuilder.com/job-details/research-pre-training-data-san-francisco-ca--4ec0c78a-e9c8-4132-9c05-022831bf8724

## About the Role

Artificial Intelligence (AI), Data Sets, Machine Learning, Data Quality, Quality Metrics, Diversity, Analysis Skills, Data Processing, Licensing, Risk Management, * 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 - we encourage you to apply even if you don't meet all preferred qualifications, but at least some:

 * A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs.
 * Experience with curation, preprocessing, and analysis of large-scale text, code, or multimodal datasets.
 * Prior experience in data engineering, dataset construction, or large-scale web data processing for machine learning models.
 * Experience evaluating or improving training data quality and knowledge of data ethics, safety, and licensing frameworks relevant to AI dataset creation.
 * 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.

## Description

The role of pre-training researchers sits at the core of our roadmap. This work blends research with large-scale data engineering to help assemble the pre-training datasets and data systems that underpin the next generation of AI models. You'll design and implement methods for sourcing, curating, and analyzing pre-training data for quality and performance., * Design and implement techniques for curating, sourcing, and filtering large-scale text, code, and multimodal data.

 * Develop data quality metrics and analysis to measure coverage, diversity, and representativeness across sources.
 * Collaborate with research and infrastructure teams to scale data processing systems efficiently and reproducibly.
 * Investigate and mitigate data risks, including privacy, safety, and licensing concerns, to ensure responsible and ethical data use.
 * Continuously evaluate dataset improvements by analyzing their downstream effects on model learning and behavior.
 * Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia.