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Binance Accelerator Program - LLM Model Training & Data Processing

AsiaRemote

AI Summary

Supports training and evaluation of LLMs, builds data annotation pipelines, and collaborates with research and engineering teams to improve model performance and tooling for AI agents in a fixed-term accelerator program.

About this role

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About Binance Accelerator Program
Binance Accelerator Program is a concise fixed-term program designed for Early Career Talent to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the worlds’ leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about BAP Program HERE
Who may apply
Current university students and recent graduates

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.

    • Requirements

  • Currently pursuing or recently completed a Degree in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. PHD is Bonus.
  • 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.

    • Skills

    Data AnalysisData Annotation PipelinesExperiment DesignFine-tuningIntegration With External ToolsLabeling GuidelinesLLMs (e.g., LLaMA, Qwen)LLM TrainingLoRAMemory ModulesModel Evaluation TechniquesPlanning StrategiesPrompt EngineeringQLoRAQuality Control ProcessesSchema DefinitionTransformer Models

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