[Career Fair] Data Scientist Mid/Senior
Indexed description
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 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.
- 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).
- Role based in Singapore office, with occasional travel (up to 1 trip per year) for conferences, research collaborations, or business meetings.
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