Job Description

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is

a place to do great work

, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also

a great place to work,

providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

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Key Responsibilities

Design, train, and evaluate reinforcement learning agents using frameworks such as Gym or Unreal engine. Implement and test reward functions, policy optimization techniques, and training pipelines. Conduct experiments to measure agent performance and learning efficiency. Collaborate with mentors to refine models and interpret experimental data. Document processes, findings, and insights.

Learning Objectives

Gain hands-on understanding of reinforcement learning algorithms (Q-learning, PPO, DQN, etc.). Learn to design training environments, rewards, and evaluation metrics. Build practical skills in debugging, experiment tracking, and model improvement. Develop the ability to connect theoretical RL concepts with real-world AI applications.

Candidate Requirements

Currently pursuing a Bachelor's or Master's degree in Computer Science, AI, or related fields. Proficiency in Python and familiarity with machine learning fundamentals. Coursework or experience in reinforcement learning or simulation-based AI is advantageous. Strong analytical thinking, curiosity, and self-motivation. Able to commit to a 6 months, full-time internship from Jan - Jun 2026

Pre-Requisites :

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Are you game?