## Senior Data Scientist (Generative AI)Apply: Singapore: Full time: Posted Today: JR2026006987Joining 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 designing and developing GenAI-driven solutions for interactive systems and developer-facing tools. The ideal candidate will have strong expertise in GenAI technologies, including large language models, retrieval-augmented generation (RAG), and agentic workflows, with experience building scalable and production-ready AI services. This role involves working closely with data engineers, software engineers, and game developers to deliver robust AI tools, manage production pipelines, and enable fast iteration in real-world environments.**Essential Duties and Responsibilities*** Design, develop, and maintain GenAI solutions for developer tools and interactive applications.* Build and extend RAG-based systems, including retrieval pipelines, indexing strategies, and prompt orchestration.* Develop agentic workflows and GenAI packages to support reasoning, planning, and tool-based execution patterns.* Collaborate with software engineering teams to design and manage production pipelines for GenAI microservices.* Work with data engineering teams to define data schemas, ingestion pipelines, and validation strategies for structured and unstructured data used by GenAI systems.* Fine-tune and adapt large language models for domain-specific tasks and performance requirements.* Partner with AI engineers to evaluate GenAI system performance using task-specific metrics, benchmarks, and qualitative analysis.* Optimize GenAI services and pipelinesfor latency, scalability, reliability, and cost efficiency in production environments.* Assist in the deployment, monitoring, and maintenance of GenAI services in cloud-based infrastructures.* Document system designs, workflows, experiments, and implementation details for internal knowledge sharing.* Stay updated on emerging trends and advancements in GenAI, LLMs, and agent-based systems through research and experimentation.* Consider ethical, legal, and regulatory implications in the development and deployment of AI systems.## Pre-Requisites :**Qualifications*** Proven experience in developing and deploying applied machine learning or Generative AI systems in real-world applications.* Proficiency in Python; experience with additional languages is a plus.* Strong understanding of LLMs, prompt engineering, retrieval systems, and agent-based architectures.* Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.* Experience building and evaluating RAG pipelines, GenAI tools, or AI-powered microservices.* Familiarity with cloud-based AI platforms and production ML workflows for training, evaluation, and deployment.* Ability to evaluate and optimize model performance using task-specific metrics and benchmarks.* Strong analytical and problem-solving skills.* Excellent written and verbal communication skills across technical and non-technical teams.**Preferred*** Experience building RAG microservices, agent frameworks, or modular GenAI tooling.* Exposure to multi-GPU training, distributed experiments, or large-scale model fine-tuning.* Experience with AWS SageMaker or similar managed ML platforms.* Awareness of emerging GenAI techniques, including tool-using agents, function calling, and planning-based workflows.**Education & Experience*** Master’s or PhD in a relevant field (Computer Science, AI, Machine Learning, etc.).* 2+ years of applied experience in machine learning or Generative AI (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.