Fine Tuning/Post Training Data Scientist

Fine Tuning/Post Training Data Scientist - RL (GRPO, PPO, RLHF)

Location: Asia / Australia, Brisbane / Australia, Melbourne / Australia, Sydney / Hong Kong / Taiwan, Taipei / New Zealand, Auckland / New Zealand, Wellington
Department: Engineering Data Science/AI
Employment Type: Full-time: Remote

Binance is a leading global blockchain ecosystem behind the worlds largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 280 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, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

You will develop and optimize Reinforcement Learning (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 RLcovering policy optimization, reward modeling, and planningpaired 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.

• Research and develop state-of-the-art RL algorithms, focusing on large model optimization and alignment techniques.
• Design and implement RL training pipelines, including environment simulation, data generation, and reward function design.
• Apply Reinforcement Learning methods to enhance LLM/VLM/Agentic AI capabilities in reasoning, planning, and autonomous decision-making.
• Collaborate with Engineers and researchers to integrate RL solutions into enterprise AI platforms.
• Monitor model performance in production and continuously improve through iterative training and fine-tuning.

• Masters Degree in Computer Science, Applied Mathematics, Machine Learning, or related fields.
• 5 years of hands-on experience in RL and [either 1: 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.

• Shape the future with the worlds 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.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.