Research, Pre-Training Data
San Francisco, CA$350k - $475kFull-timePosted 11mo ago
About the role
Role focusing on designing and implementing methods for sourcing, curating, and analyzing pre-training data at scale, blending research with data engineering to support next-generation AI models.
Responsibilities
- 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.
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.
Skills
Required:PythonDeep Learning FrameworksDistributed Training Debugging
Nice to have:Data Curation & AnalysisData Ethics & Licensing
Benefits
- generous health, dental, and vision benefits
- unlimited PTO
- paid parental leave
- relocation support as needed
Last updated Jul 8, 2026. Interested? Apply on the company site.
About Thinking Machines Lab
Connectionism: Research Blog by Thinking Machines Lab
Thinking Machines Lab is an artificial intelligence research and product company. We’re building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.
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