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Data Scientist

Razer

Singapore

On-site

SGD 70,000 - 100,000

Full time

Today
Be an early applicant

Job summary

A leading gaming technology company in Singapore is seeking a Data Scientist to integrate external AI tools into their internal systems. The role requires a minimum of 1 year in applied AI/ML, strong Python skills, and experience with LLM APIs. Candidates should have a passion for gaming and be comfortable in a fast-paced environment. The position offers an opportunity to work on cutting-edge AI technologies in a collaborative team setting.

Qualifications

  • Minimum 1 year of hands-on experience in applied AI/ML or AI integration.
  • Strong proficiency in Python and software engineering fundamentals.
  • Proven experience working with LLM APIs and AI SDKs.

Responsibilities

  • Build and maintain internal tooling for AI integration.
  • Develop and optimize in-house AI/ML models.
  • Evaluate and prototype external AI solutions.

Skills

Applied AI/ML experience
Python proficiency
Experience with LLM APIs
Cloud environments familiarity
Debugging and testing AI services

Education

Bachelor’s or Master’s degree in Computer Science, AI, ML, or related

Tools

LangChain
Hugging Face
AWS
GCP
Azure
Job description

This Data Scientist role sits within the Applied AI Pod, focused on evaluating, integrating, and scaling 3rd-party AI tools into Razer’s internal AI stack. You will play a critical role in building robust, scalable systems that bridge external AI solutions with our internal infrastructure to enable intelligent, real-time capabilities across gaming and platform experiences.

The ideal candidate is a technically strong generalist with a strong grasp of applied AI/ML, experience working with external AI APIs (e.g., GenAI, vision, speech) and skilled in implementing and adapting AI solutions into production-grade systems. You will collaborate closely with AI Software Engineers, Data Scientists, and DevOps engineers to extend Razer’s AI capabilities through reliable, high-performance integration work.

Job Description
  • Build and maintain internal tooling, pipelines, and wrappers to integrate external AI services (LLMs, speech, vision, agents) into Razer's ecosystem
  • Develop and optimize lightweight in-house AI/ML models to enhance and complement 3rd-party tools
  • Evaluate and prototype external AI solutions, focusing on code-level integration, architecture compatibility, and system performance
  • Conduct benchmarking, trade-off analysis, and technical validation for external APIs and platforms
  • Collaborate with software engineering and DevOps to ensure secure, production-ready, and scalable deployments
  • Stay up to date with the latest developments in AI SDKs, APIs, toolchains, and deployment strategies
Prerequisites
Technical Skills:
  • Minimum 1 year of hands-on experience in applied AI/ML, AI systems engineering, or AI integration
  • Strong proficiency in Python and software engineering fundamentals, including experience with API design, data structures, and modular codebases
  • Proven experience working with LLM APIs (e.g., OpenAI, Claude, Gemini), AI SDKs, and toolchains such as LangChain, Hugging Face, or RAG frameworks
  • Experience integrating external AI APIs into internal platforms with attention to latency, throughput, and reliability
  • Familiarity with cloud environments (AWS, GCP, or Azure) and MLOps workflows (e.g., model deployment, versioning, CI/CD for ML systems)
Preferred Qualifications
  • Exposure to vector databases, prompt engineering, or agent-based architectures is a plus
  • Strong ability to debug, test, and validate AI services in production environments
  • Ability to clearly communicate technical decisions and trade-offs across engineering and AI teams
  • Passion for gaming and interest in using AI to enhance user experiences is a plus
  • Comfortable working in fast-paced, high pressure, agile environment.
Education & Experience
  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline
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