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Binance

Posted 18 months ago

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Data Scientist（LLM）

TaipeiOn-siteFull-time

AI Summary

Data Scientist focused on researching and improving LLM technologies, including fine-tuning, RAG, prompt engineering, and knowledge-grounded dialogue systems for Binance’s products.

About this role

Binance is the leading global blockchain ecosystem and cryptocurrency infrastructure provider whose suite of financial products includes the world’s largest digital-asset exchange.
Our mission is to accelerate cryptocurrency adoption and increase the freedom of money.

If you’re looking for a fast-paced, mission-driven organization where opportunities to learn and excel are endless, then Binance is the place for you.


Responsibilities:

  • Conduct research on cutting-edge LLM technologies, including but not limited to: large language models and fine-tuning techniques, retrieval-augmented generation (RAG), prompt engineering, and knowledge-grounded dialogue systems.
  • Enhance overall performance for foundation models, encompassing data acquisition, model evaluation, SFT, reward modeling, and reinforcement learning.
  • Explore new downstream products with AI and AI agent technologies at their core for Binance products.
  • Stay up-to-date with the latest academic and industrial advancements in AI, LLMs, etc.

    • Qualifications:

  • Master’s or PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
  • At least 3-5 years of relevant industry experience in developing Machine Learning models at scale from inception to business impact
  • Research experience in LLMs, multi-modal understanding, vision and language, and other related topics.
  • Highly competent in algorithms and programming; strong coding skills in Python, C/C++, etc.

    • Preferred Qualifications
  • Experience in NLP and LLM technologies.
  • Publications in top-tier venues, such as KDD, CVPR, NeurIPS, ICLR, ICML, EMNLP, ACL, ECCV, ICCV, etc.

    • Skills

    C/C++Data AcquisitionDeep LearningFine-tuningKnowledge-grounded DialogueLLMMachine LearningModel EvaluationMulti-modal UnderstandingPrompt EngineeringPythonRAGReinforcement Learning From Human FeedbackSFT

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