Senior Data Scientist - #1172959

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.

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.