Responsibilities:

📍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 RL 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.

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.

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