Senior Video AI Researcher (Foundation Models)

L&Q OASIS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tencent's Lightspeed Tech Center seeks a top-tier AI researcher to design and advance next-generation video generation foundations. You will push the boundaries of long-video architectures, tokenizers, and multi-resolution modeling while leading large-scale pre-training efforts and publishing key findings.

The role demands a PhD in AI-related fields, deep diffusion model expertise, and extensive experience with PyTorch and distributed training.

Qualifications

• Ph.D. in AI-related fields with first-author papers at top-tier conferences.
• Proficient in the principles and engineering implementation of diffusion models and autoregressive generation.
• Experience training video/image generation models from scratch; highly proficient in PyTorch and large-scale distributed training.
• Deep understanding of the design trade-offs in Video VAE/Tokenizers, with 3+ years of relevant research experience.
• Publications related to video generation or diffusion models.
• Experience leading end-to-end video foundation model projects is preferred.

Responsibilities

• Design and iterate on the next-generation video generation foundation architecture.
• Explore core technologies for long video generation and multi-resolution modeling.
• Lead video pre-training at large token scale, defining data mixture and curriculum learning strategies.
• Publish academic papers and drive technical roadmap decisions based on state-of-the-art results.
• Track industry developments and run comparative experiments to guide product roadmaps.

Skills

Diffusion models

Autoregressive generation

PyTorch

Distributed training

Video generation

Education

Ph.D. in AI-related fields

Tools

Video VAE

Tokenizers

Job description

Tencent's Lightspeed Tech Center seeks a top-tier AI researcher to design and advance next-generation video generation foundations. You will push the boundaries of long-video architectures, tokenizers, and multi-resolution modeling while leading large-scale pre-training efforts and publishing key findings.

The role demands a PhD in AI-related fields, deep diffusion model expertise, and extensive experience with PyTorch and distributed training.