Multimodal GenAI Research Scientist

TikTok Inc.; San Jose (CA); On-site; USD 254,000 - 588,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) matching

Paid parental leave

Long-term disability

Job summary

TikTok Inc. is seeking a PhD-level researcher to advance generative AI and multimodal foundation models for the TikTok platform.

You will drive end-to-end creative AI workflows, from research to production, focusing on image/video generation, efficient model design, and agentic systems. Role emphasizes large-scale training, post-training techniques (SFT/RL), and reinforcement learning improvements to scale capabilities for real-world creation scenarios.

Qualifications

• PhD in software development, computer science, computer engineering, or related technical discipline.
• Proficiency in training generative AI or large models using frameworks such as PyTorch or JAX.
• Strong programming skills and solid fundamentals in machine learning.
• Strong problem-solving ability and motivation to tackle real-world challenges.
• Good communication and collaboration skills in fast-paced environments.

Responsibilities

• Conduct research and development in generative AI and multimodal models (e.g., image, video).
• Develop large-scale foundation models (LLMs/VLMs), through post-training techniques.
• Design and build models for creative applications on the TikTok platform, driving end-to-end impact from research to production through cross-functional collaboration.
• Explore new AI-driven product opportunities and contribute to next-generation creative experiences.

Skills

GenAI training

PyTorch/JAX

Programming fundamentals

Machine learning

Collaboration

Education

PhD in CS/Software Eng or related

Tools

PyTorch

JAX

Job description

TikTok Inc. is seeking a PhD-level researcher to advance generative AI and multimodal foundation models for the TikTok platform.

You will drive end-to-end creative AI workflows, from research to production, focusing on image/video generation, efficient model design, and agentic systems. Role emphasizes large-scale training, post-training techniques (SFT/RL), and reinforcement learning improvements to scale capabilities for real-world creation scenarios.