Research, Pre-Training Data
Thinking Machines Lab · San Francisco
Frontier labonsite$350k–$475k
At a glance
Highlights
- Design methods for sourcing and curating frontier pre-training datasets.
- Evaluate dataset improvements via downstream model learning and behavior.
- Publish research and share datasets advancing the wider AI community.
What they offer
- Generous health, dental, and vision benefits
- Unlimited PTO
- Paid parental leave
- Relocation support as needed
Ideal candidate
A curious researcher-engineer drawn to data, ML, and systems who wants to shape how frontier models learn and openly share code, datasets, and insights with the community.
Requirements
- 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 related discipline
- Clarity in communication and ability to explain complex technical concepts in writing
- Strong grasp of probability, statistics, and ML fundamentals
- 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
- Contributions to open datasets, research publications, or data tooling
- visa sponsorship
- We sponsor visas
Lab profile
About Thinking Machines Lab
Builds frontier AI that extends human will and judgment through customizable models and interfaces.
What they build
- Inkling frontier models
- Tinker model customization
- Human-AI communication interfaces
Known for
- Frontier model training
- Post-training and reinforcement learning
- Evaluation infrastructure
- GPU supercomputing and reliability
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