Multimodal Controllable Video Gen Researcher

LightSpeed Studios

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+
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Job summary

LightSpeed Studios in Singapore seeks a PhD-level researcher to advance controllable video generation for interactive gaming. You will design multimodal frameworks and pursue high-fidelity results under sparse control signals, collaborating with engine teams to define interfaces for controllable signals.

The role emphasizes research in camera, trajectory, and posture control, real-time performance, and integration with reinforcement learning post-training. Prior game AI experience is a plus.

Qualifications

  • PhD in a relevant AI field with strong publication record.
  • Proficient in conditional generation models and multi-player/multi-channel control technologies.
  • Familiar with diffusion model principles.

Responsibilities

  • Design a multimodal controllable generation framework for inputs like keyboard, controller, trajectory and voice.
  • Research high-fidelity generation with sparse control signals; extend conditional control paradigms in video.
  • Decouple and integrate trajectory, camera, motion, and posture controls.
  • Develop dedicated control modules for different game genres.
  • Build video generation capabilities for multi-player collaboration with low latency.
  • Collaborate with Engine/Agent teams to define standardized interfaces for controllable signals.
  • Drive joint optimization of controllable generation and RL post-training.

Skills

PhD in AI/Computer Vision
Conditional generation & diffusion
Multichannel control & gameplay
Camera/trajectory/posture control
Engine I/O & frame sync
Python/PyTorch publications
Real-time video generation
Game AI / game development

Education

PhD in AI/Computer Vision/Deep Learning

Tools

Python/PyTorch

Job description

LightSpeed Studios in Singapore seeks a PhD-level researcher to advance controllable video generation for interactive gaming. You will design multimodal frameworks and pursue high-fidelity results under sparse control signals, collaborating with engine teams to define interfaces for controllable signals.

The role emphasizes research in camera, trajectory, and posture control, real-time performance, and integration with reinforcement learning post-training. Prior game AI experience is a plus.

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