- 7500B BEACH ROAD Central Region (Singapore) Singapore
Working Location
Job Description
Responsibilities
Reward Design & Long-Term Decision Making: Develop effective reward mechanisms and solve long-term credit assignment challenges by connecting an agent’s short-term decisions with delayed outcomes, such as customer satisfaction, product returns, and user retention.
User Modeling & Adaptive Agent Behavior: Design systems that can understand changing user preferences and behaviors, manage uncertainty, and determine the appropriate response, including asking questions, making recommendations, taking actions, or waiting for more information.
Policy Optimization & Evaluation: Develop reliable offline evaluation methods, establish strong experimental baselines, and conduct ablation studies to measure and improve agent performance. Explore advanced RL techniques as more real-world data becomes available.
Research & Engineering Collaboration: Work closely with infrastructure and engineering teams to transform complex product challenges into research problems and implement research ideas as testable agent behaviors in real-world production environments.
Reinforcement Learning Expertise: Strong research experience in Reinforcement Learning, with a track record of applying RL techniques to practical, real-world problems.
Programming & ML Skills: Strong proficiency in Python and hands-on experience with modern ML/RL frameworks such as PyTorch, JAX, or similar tools.
If interested, please submit your application to ************* with your expected salary and resume.
We regret that only short-listed candidates will be contacted shortly. By submitting your application or resume, you agree to the collection, use, retention, and sharing of your personal information with potential employers for their assessment.
JDA WMS Pte Ltd | EA Personnel: Pham Thi Tuyet Mai
EA License No: 23S1595 | EA Registration No: R25127838
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