Binance Accelerator Program - LLM Model Training & Data Processing

About the 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, and more. Our mission is to increase the freedom of money and financial access for people around the world. 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. Why Binance · Shape the future of finance · Collaborate with world-class talent in a user-centric global organization with a flat structure · Tackle challenging projects in a fast-paced and innovative enviornment with autonomy · Thrive in a results-driven workplace with opportunities for career growth and continuous learning · Competitive salary and company benefits · Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team) Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success. By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice . We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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.
• —· 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.

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.
• —· Shape the future of finance

Skills