Thinking Machines Lab

Research, Post-Training Data

San Francisco

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

PythonExpressMachine LearningDeep LearningTensorFlowPyTorchData EngineeringLLMsStatisticsA/B TestingLogisticsResearchCommunication

About the role

The role of post-training researchers sits at the core of our roadmap.
This is the critical bridge between raw model intelligence and a system that is actually useful, safe, and collaborative for humans.
Post-training data research work sits at the intersection of human insight and machine learning.

Design and execute data collection and synthesis strategies for post-training by combining human feedback, preference data, and synthetic examples to guide model behavior.
Develop pipelines and frameworks for scalable, high-quality human labeling, model-assisted labeling, and synthetic data generation.
Design and evaluate metrics and benchmarks that measure data quality, alignment, and the real-world impact of post-training interventions.
Scale and explore: post-training will involve a combination of scaling the existing methodologies and developing new ones.
Ability to design, run, and interpret experiments with scientific rigor and clarity.

Strong engineering skills, ability to contribute code and debug in complex codebases.
Experience with data curation, human feedback, or synthetic data generation for large language models or similar systems.
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 managing or analyzing human data collection campaigns or large-scale annotation workflows.
Research or engineering contributions in alignment, data-centric AI, or human-AI collaboration.
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.
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.