Senior Data Scientist

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. • 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 pipelines for 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.