Biomedical Scientist jobs in United Kingdom

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.

• 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

• 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)

• 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.

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