Hunyuan Multimodal Algorithm Researcher (omni-modal)​​

Tencent

Palo Alto, California, US
Base: $134,900.00 to $253,400.00 py; bonus/equity:...
Not specified (assumed to be hybrid based on job location and industry trends).
Experience with large-scale multimodal data processing
Solid foundation in deep learning algorithms
Proficiency in model tuning for training/inference
Tencent is seeking a Hunyuan Multimodal Algorithm Researcher in Palo Alto, California, to contribute to the development of large multimodal models through R&D and optimization. The ideal candidate will possess a strong background in deep learning, multimodal data processing, and model architecture

Job Summary

  • The role involves conducting research and development of Omni multimodal large models.
  • You will analyze challenges in R&D and devise solutions to enhance model performance.
  • Tencent fosters an environment where diverse voices fuel innovation and support employee growth.

Matching Summary

Match Score: 85

Tencent is seeking a Hunyuan Multimodal Algorithm Researcher in Palo Alto, California, to contribute to the development of large multimodal models through R&D and optimization. The ideal candidate will possess a strong background in deep learning, multimodal data processing, and model architecture.

Salary

Base: $134,900.00 to $253,400.00 per year; Bonus/Equity: Not specified; Benefits: Medical, dental, vision, life and disability benefits

Skills & Requirements

Must-have

  • Experience with large-scale multimodal data processing
  • Solid foundation in deep learning algorithms
  • Proficiency in model tuning for training/inference

Nice-to-have

  • Familiarity with Diffusion Models and Autoregressive Models
  • Participation in ACM or NOI competitions
  • Strong communication skills and teamwork

Key Requirements

  • Bachelor’s degree or higher in relevant fields
  • Hands-on experience in multimodal data processing
  • Publication in top-tier conferences preferred

Work Rights

Not specified

Tailored Resume

Cover Letter