About this role

▸about Binance — company background

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

About the Role

For all students looking to gain hands-on experience! You'll work directly with senior scientists on research problems at the frontier of LLM reasoning, post-training methodology, and agentic AI — applied to global crypto markets. Your work has a direct path to production systems serving hundreds of millions of users, and where findings warrant it, a clear path to external publication.

You run experiments, implement ideas from recent research, synthesize papers into hypotheses, and work with engineers to understand how research translates to real systems.

This is not a purely literature-review or passive research role. You are expected to think independently and generate insight.

Responsibilities

• Contribute to the design and execution of experiments in reasoning model training, post-training alignment, test-time scaling, or systematic model evaluation — with a focus on applications in financial and crypto-native contexts

• Review and synthesize recent academic literature at NeurIPS, ICML, ICLR, and ACL — tracking developments in reasoning, alignment, and agentic AI to inform and sharpen ongoing research directions

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