Razer Logo

Razer

Manager, Data Scientist

Reposted 3 Months Ago
Be an Early Applicant
In-Office
Singapore, SGP
Mid level
In-Office
Singapore, SGP
Mid level
Lead a team to design, develop, and deploy reinforcement-learning and agent-based systems for games. Define technical roadmaps, drive R&D across RL/imitation/planning, establish evaluation frameworks, scale training and production pipelines, and collaborate cross-functionally to integrate robust, generalizable autonomous agents.
The summary above was generated by AI

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 will focus on leading the development of intelligent autonomous systems for game developers and players. The ideal candidate will have strong expertise in reinforcement learning (RL) and agent-based modeling, along with the ability to apply a broad range of AI techniques to build robust gameplay agents and adaptive in-game behaviors. This role involves working closely with AI engineers, game developers, and software engineers to deliver scalable, production-ready intelligent systems that enhance exploration, automation, and fast iteration across diverse gaming environments.

Essential Duties and Responsibilities

  • Lead and mentor a team developing intelligent gameplay agents and autonomous systems for in-house AI services.
  • Define the technical roadmap for agent-based intelligence, supporting multiple game engines, genres, and gameplay objectives.
  • Drive research and development across reinforcement learning, imitation learning, planning, and hybrid approaches as needed.
  • Ensure agent solutions are robust, generalizable, and scalable across diverse game mechanics and player behaviors.
  • Establish evaluation frameworks and success metrics for autonomy, task success, stability, and real-world performance.
  • Collaborate with engineering teams to support deployment, integration, and scaling of intelligent agents into production pipelines.
  • Promote best practices in experiment tracking, reproducibility, and large-scale training workflows.
  • Communicate technical progress, trade-offs, and long-term strategy effectively to cross-functional stakeholders.
  • Stay updated with advancements in intelligent systems, including multi-agent learning, agentic AI, and adaptive decision-making.

Pre-Requisites :

Qualifications

  • Proven experience leading or mentoring teams building autonomous agents or applied AI systems.
  • Strong proficiency in Python; experience with C++ or Rust is a plus.
  • Strong foundation in reinforcement learning methods (policy-based, value-based, actor-critic) and agent training workflows.
  • Familiarity with simulation environments and game engines (e.g., OpenAI Gym, Unity, Unreal Engine).
  • Experience scaling experimentation, training pipelines, and evaluation processes for agent-based systems.
  • Strong analytical, debugging, and problem-solving skills in complex AI systems.
  • Excellent communication and collaboration skills across technical and non-technical stakeholders.

Preferred
 

  • Experience with multi-agent systems, self-play, adversarial training, or population-based methods.
  • Exposure to imitation learning, offline RL, planning-based agents, or hybrid autonomy approaches.
  • Experience integrating agent services via APIs, RabbitMQ, gRPC, or REST-based microservices.
  • Familiarity with experiment management, reproducibility tooling, and evaluation automation.
  • Background in gaming AI, robotics, simulation, or control systems is a plus.

Education & Experience

  • Master’s or PhD in a relevant field (Computer Science, AI, Machine Learning, etc.).
  • 3+ years of applied experience in reinforcement learning, agent-based AI, or intelligent autonomous systems, including demonstrated leadership responsibilities (academic or industry).

Travel Requirements

Role based in Singapore office, with occasional travel (up to 1 trip per year) for conferences, research collaborations, or business meetings.

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?

Razer Singapore, Singapore, SGP Office

Singapore, Singapore

Similar Jobs

3 Months Ago
Hybrid
Singapore, SGP
Senior level
Senior level
eCommerce • Financial Services
Lead pricing-focused data science for on-demand services: translate business problems into ML solutions, own full ML lifecycle, improve dynamic pricing using econometrics and causal inference, design experiments, monitor models, and communicate results to stakeholders.
Top Skills: AlicloudAWSDockerGCPGitJupyterPythonSQL
Yesterday
In-Office
Singapore, SGP
Entry level
Entry level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develops semiconductor memory reliability test flows, qualification plans, and manufacturing test strategies for HBM products. The role investigates reliability and RMA failures using electrical and physical failure analysis, drives root-cause resolution, supports process conversions, manages technical risks, and collaborates across fab, design, technology, systems, and quality teams. It also applies machine learning and AI automation to reliability data and workflows.
Top Skills: Agentic AiArtificial IntelligenceClaude CodeCmosDramJmpMachine LearningPython
Yesterday
In-Office
Singapore, SGP
Mid level
Mid level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develop and deploy predictive models and AI/agentic AI solutions using large-scale manufacturing data. Perform EDA, data extraction/cleansing, feature engineering, and statistical modeling. Collaborate with data engineers, manufacturing engineers, UX, and stakeholders to translate insights into operational improvements that boost yield, quality, efficiency, and business value.
Top Skills: Agentic AiAIPythonRSQL

What you need to know about the Singapore Tech Scene

The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account