Position: Research Scientist (RS) – Reinforcement Learning & AI Algorithm Development
Location: On-site, 5 days per week (no remote option)
Reports to: Head of Data Team

QUALIFICATIONS

Educational Background
PhD in Computer Science, Applied Mathematics, Statistics, or a related field (with a focus on Reinforcement Learning or dynamic system optimization), OR
Master’s degree with 5+ years of full-time AI research experience.
Research & Deployment Experience

ROLE OVERVIEW

We are seeking a Research Scientist (RS) with deep expertise in Reinforcement Learning (RL) and advanced AI algorithm development. In this role, you will design, prototype, and deploy state-of-the-art ML/AI solutions for diverse applications, from user behavior modeling and real-time optimization to anomaly detection and multi-agent systems. You will collaborate closely with cross-functional teams in a fast-paced, on-site environment, driving both research and product impact.

KEY RESPONSIBILITIES

Algorithm Research & Development
Lead the research, prototyping, and refinement of advanced RL and AI algorithms (e.g., multi-agent collaboration, real-time optimization, anomaly detection).
Conduct daily code reviews and performance optimizations with Machine Learning Engineers.
Maintain clean, well-documented code and contribute to best practices for reproducible research.
On-site Cross-Functional Collaboration
Work on-site with product managers, data engineers, and other stakeholders to align AI solutions with business objectives and technical constraints.
Provide expert guidance on the feasibility and scalability of proposed AI features or improvements.
Research Output & Thought Leadership
Contribute to internal technical standards, best practices, and AI/ML frameworks.
Mentor junior researchers and engineers, sharing knowledge on cutting-edge RL/AI techniques.