Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users.
You will develop and optimize RL models for enterprise-scale applications such as customer service, token reporting, compliance, and Web3 domain reasoning.
You will explore and evaluate advanced algorithms including PPO, GRPO, DPO, RLHF, RLAIF, and Agentic RL to enhance the capabilities of LLMs, VLMs, and Agentic AI at Binance.
The role requires a strong theoretical foundation in RL—covering policy optimization, reward modeling, and planning—paired with the engineering skills to build scalable production systems.
You will take full ownership from research through deployment, driving experimentation with systematic evaluation and benchmarking.
Collaboration across research, infrastructure, and application teams will be key to delivering impactful AI solutions.
Requirements
Master’s degree in Computer Science, Applied Mathematics, Machine Learning, or related fields.
3+ years of hands-on experience in RL or LLM/VLM/Agentic AI optimization.
Strong coding skills in Python, with experience in ML frameworks and RL libraries.
Experience with large-scale distributed training and optimization.
Self-driven, ownership mindset, and strong problem-solving skills. Excellent communication skills for cross-functional collaboration.