Expert In Reinforcement Learning
4 days ago
About the Role
As a seasoned expert in Reinforcement Learning, you will be responsible for developing and optimizing RL models for large-scale enterprise applications such as customer service, token reporting, compliance, and Web3 domain reasoning.
This role requires a strong theoretical foundation in RL, covering policy optimization, reward modeling, and planning, paired with engineering skills to build scalable production systems. You will take full ownership from research through deployment, driving experimentation with systematic evaluation and benchmarking.
Responsibilities:
Research and develop cutting-edge 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 RL methods to enhance Large Language Models (LLMs), Vision-Language Models (VLMs), and 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.
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.
Why Join Us
• Shape the future with our 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)
We are committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
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