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 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
