
Senior Data Scientist
2 days ago
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**:
This Senior Data Scientist role sits within the AI Integration 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.
**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
**Pre-Requisites**:
**Pre-Requisites**
**Technical Skills**:
- Minimum 3 years 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
**Are you game?
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