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 :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.Responsibilities include:
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
Technical Skills:
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
Are you game?
Top Skills
Razer Singapore Office
1 One-north Cres, Singapore, 138538
