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Research, Pre-Training Data

📅 Aug 4
PythonDeep Learning FrameworksData EngineeringMachine Learning

📜 Description

  • 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.

🛠️ Requirements

  • 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.
  • Clarity in communication, with the ability to explain complex technical concepts in writing.
  • A strong grasp of probability, statistics, and ML fundamentals.
  • 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.

Benefits

  • Dental
  • Vision benefits
  • Unlimited PTO
  • Paid parental leave
  • Relocation support as needed
Thinkingmachines

Research, RL Scaling

Thinkingmachines👥 51 - 200 employees🏢 Technology
🕒 14 days ago

This role focuses on scaling reinforcement learning for frontier models, requiring expertise in asynchronous RL algorithms and the integration of training and inference systems.

PythonDeep Learning FrameworksReinforcement LearningAsynchronous RL Algorithms

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