Binance Accelerator Program - LLM Model Training & Data Processing
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Large Language Models
Binance Accelerator Program - LLM Model Training & Data Processing
from 🇮🇳 India | 🇸🇬 Singapore | 🇯🇵 Japan | 🇹🇠Thailand | 🇨🇳 China | 🇮🇩 Indonesia | 🇧🇩 Bangladesh | 🇮🇷 Iran | 🇯🇴 Jordan | 🇰🇿 Kazakhstan | 🇲🇾 Malaysia | 🇳🇵 Nepal | 🇵🇰 Pakistan | 🇵🇠Philippines | 🇰🇷 South Korea | 🇱🇰 Sri Lanka | 🇹🇼 Taiwan | 🇹🇷 Turkey | 🇻🇳 Vietnam | 🇱🇧 Lebanon | 🇲🇲 Myanmar | 🇱🇦 Laos | 🇾🇪 Yemen | 🇲🇻 Maldives | 🇴🇲 Oman
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.