Binance Accelerator Program - LLM Model Training & Data Processing at Binance
Sydney, New South Wales, Australia -
Full Time


Start Date

Immediate

Expiry Date

25 Nov, 25

Salary

0.0

Posted On

26 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

English, Machine Learning, Computer Science, Artificial Intelligence

Industry

Information Technology/IT

Description

Binance is the global blockchain company behind the world’s largest digital asset exchange by trading volume and users, serving a greater mission to accelerate cryptocurrency adoption and increase the freedom of money.
Are you looking to be a part of the most influential company in the blockchain industry and contribute to the crypto-currency revolution that is changing the world?

REQUIREMENTS:

  • Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline.
  • Solid understanding of machine learning and deep learning fundamentals.
  • Familiarity with transformer models, LLMs (e.g., LLaMA, Qwen), or related technologies is a strong plus.
  • Experience or interest in prompt engineering, fine-tuning methods (e.g., LoRA, QLoRA), and model evaluation techniques.
  • Basic knowledge of data annotation workflows and labeling tools.
  • Strong analytical and problem-solving skills; able to work both independently and collaboratively.
  • Fluency in English is required to be able to coordinate with overseas partners and stakeholders. Additional languages would be an advantage.
Responsibilities
  • Assist in the training, fine-tuning, and evaluation of Large Language Models (LLMs) using public and in-house datasets.
  • Support the development and optimization of AI agents, including prompt engineering, memory modules, planning strategies, and integration with external tools.
  • Design, implement, and manage data annotation pipelines, including schema definition, labeling guidelines, and quality control processes.
  • Work closely with research and engineering teams to improve model performance, scalability, and robustness.
  • Conduct experiments, perform data analysis, and clearly document methodologies and findings.
  • Explore and test new tools, frameworks, and best practices for enhancing LLM systems and AI agent capabilities.
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