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. Binance is trusted by more than 320 million people in 100+ countries for its industry-leading security, transparency, trading engine speed, protections for investors, and unmatched portfolio of digital asset products and offerings from trading and finance to education, research, social good, payments, institutional services, and Web3 features. Binance is devoted to building an inclusive crypto ecosystem to increase the freedom of money and financial access for people around the world with crypto as the fundamental means.

About Binance Accelerator Program Binance Accelerator Program (BAP) is a 3-6 month internship program designed for Early Career talent to have firsthand experience in the rapidly expanding digital assets space. You will be given the opportunity to develop your skills at Binance and understand what it’s like to work at the world's leading blockchain ecosystem. As part of your internship in the BAP, there will also be opportunities for networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about the BAP Program HERE.

Who may apply Current university students and recent graduates. *Terms of employment / engagement shall be subject to contract and local applicable laws

Key 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.

Qualifications And 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.

Additional information

Why Binance • Shape the future with the world’s leading blockchain ecosystem • Collaborate with world-class talent in a user-centric global organization with a flat structure • Tackle unique, fast-paced projects with autonomy in an innovative environment • Thrive in a results-driven workplace with opportunities for career growth and continuous learning • Competitive salary and company benefits • Work-from-home arrangement (the arrangement may vary depending on the work nature of the business 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 confirm that you have read and agree to our Candidate Privacy Notice.

• 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.

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