Thinking Machines Lab

Research, Pre-Training Data

San Francisco

H1B sponsorship available$350k-$475kDetected 78 days ago

PythonExpressMachine LearningDeep LearningTensorFlowPyTorchData EngineeringStatisticsA/B TestingLogisticsResearchCommunication

About the role

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 work with automated pipelines and human-in-the-loop processes, contributing both scientific insight and production-grade code.

Design and implement techniques for curating, sourcing, and filtering large-scale text, code, and multimodal data.
Collaborate with research and infrastructure teams to scale data processing systems efficiently and reproducibly.

Clarity in communication, an ability to explain complex technical concepts in writing.

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.
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.
or, equivalent industry research experience.

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence.

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

Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Develop data quality metrics and analysis to measure coverage, diversity, and representativeness across sources.
Continuously evaluate dataset improvements by analyzing their downstream effects on model learning and behavior.
Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).
Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.

While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
We sponsor visas.

This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.