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 :

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 :

Are you game?

Job Requirements