Data Scientist (Reinforcement Learning) Intern

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 :

This role is ideal for candidates who are passionate about translating cutting-edge AI research into scalable, real-world products - with a particular interest in enhancing experiences for gamers. You will collaborate closely with cross-functional teams across AI, data engineering, product development, and marketing to design, prototype, and deploy intelligent systems that drive user engagement and business impact. This is a unique opportunity to contribute meaningfully to AI product innovation in a dynamic, fast-paced environment.

Key Responsibilities
• Perform discovery and research to enhance service’s performance
Design, train, and evaluate reinforcement learning agents using frameworks such as Gym or Unreal engine
• Contribute to codebases using version control best practices via GitHub
• Documentation of methodologies and codebase for knowledge sharing, general understanding, and collaboration

What we are looking for:

Proficiency in Python and familiarity with Object Oriented Programming
• Familiarity with reward functions design and policy optimization techniques
• Understand a typical reinforcement learning workflow
• Excellent verbal and written communication skills to collaborate effectively with both technical and non-technical stakeholders
• Experience using GitHub for version control, issue tracking, pull requests, code reviews, and collaborative development workflows
• Comfortable working in fast-paced, high-pressure, agile environment

What will set you apart from others:
• Familiarity with messaging services/protocols like HTTP, MQTT, and AMQP
• Understand the reward function design limitations, pitfalls, and good practices
• Understand observation space construction and optimization in a RL workflow

Qualifications:
•  Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or any related technical discipline

Pre-Requisites :

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?