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Thinking Machines LabThinking Machines LabSan Francisco, CA

Research, Pre-Training Data

Designs and implements methods for sourcing, curating, and analyzing large-scale pre-training datasets for AI models, blending research with production-grade data engineering. Requires Python proficiency, deep learning frameworks, and strong ML fundamentals.

350k – 475k/yr
On-siteML Engineering

About the role

What You’ll Do

  • 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.

Skills and Qualifications

Minimum qualifications:

  • 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.
  • 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.

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.

Skills

PythonPyTorchTensorFlowJAXMachine LearningData EngineeringDistributed TrainingStatisticsProbabilityMultimodal Data

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