R&D Engineer

XG TECH PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading tech firm in Singapore is seeking an innovative engineer to define and build next-gen intelligent 3D content creation systems. Responsibilities include researching algorithms for 3D asset generation, developing AI agents that autonomously manage 3D environments, and optimizing production pipelines. Candidates should have a Master’s or PhD in a related field with a strong programming background in Python and experience with deep learning frameworks. This role offers the opportunity to publish research and collaborate with various teams.

Qualifications

• Master's or PhD degree in relevant fields.
• Proven research background with publications in computer vision or graphics.
• Deep understanding of Deep Learning frameworks and strong Python programming skills.

Responsibilities

• Research, design, and implement algorithms for 3D generation.
• Develop AI agents that understand complex user instructions.
• Optimize generation pipelines for production readiness.
• Conduct original research and publish findings.
• Collaborate with technical artists and engineers.

Skills

Algorithm Development

Deep Learning frameworks

Programming in Python

Education

Master’s or PhD degree in Computer Science, Electrical Engineering, Mathematics

Tools

PyTorch

TensorFlow

Job description

In this role, you will define and build the next generation of intelligent 3D content creation systems. You will not only develop core algorithms for generating high-quality 3D assets but also design AI Agents capable of understanding complex user instructions, planning workflows, and autonomously manipulating 3D environments.

Key Responsibilities

• Algorithm Development: Research, design, and implement cutting-edge algorithms for text-to-3D, image-to-3D, and video-to-3D generation. Focus areas include NeRF, 3D Gaussian Splatting, geometry processing, and diffusion models.
• AI Agent Design: Develop "3D Agents" powered by Large Language Models (LLMs) that can understand semantic instructions to retrieve, generate, edit, and arrange 3D assets within a scene autonomously.
• Pipeline Engineering: Bridge the gap between research prototypes and production-ready tools. Optimize generation pipelines for inference speed, mesh topology quality, and texture resolution.
• Innovation & Publication: Keep up-to-date with the latest academic progress. Reproduce SOTA methods and conduct original research. Publishing your findings in relevant conferences or journals is strongly encouraged and supported.
• Collaboration: Work closely with technical artists, graphics engineers, and product managers to integrate generative capabilities into existing 3D workflows (e.g., Unity/Unreal/Blender plugins).

Basic Qualifications

• Education: Master’s or PhD degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• Research Background: Proven track record of publications in computer vision, computer graphics, or machine learning. Note: While top-tier venues (CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, ICLR) are a plus, we value high-quality research and distinct contributions in any relevant peer-reviewed venue.
• Technical Stack: Deep understanding of Deep Learning frameworks (PyTorch or TensorFlow) and strong programming skills in Python.