Member Of Technical Staff — Diffusion Model

Radixark

Palo Alto, CA, United States
Competitive compensation; meaningful equity includ...
On-site
5+ years ml research or applied engineering experience
Expertise in diffusion models and generative architectures
Deep understanding of deep learning optimization fundamentals
RadixArk is seeking a Member of Technical Staff specializing in diffusion models to advance generative modeling technology. The role involves deep research and engineering execution, focusing on developing and deploying cutting-edge AI models for various applications

Job Summary

  • This role combines deep research thinking with strong engineering execution to advance the frontier of generative modeling.
  • You will work on cutting-edge diffusion and flow-based models for image, video, and multimodal generation, pushing model quality, efficiency, and scalability.
  • RadixArk is an infrastructure-first company built by engineers who've shipped production AI systems and developed world-class open systems for inference and training.

Matching Summary

Match Score: 85

RadixArk is seeking a Member of Technical Staff specializing in diffusion models to advance generative modeling technology. The role involves deep research and engineering execution, focusing on developing and deploying cutting-edge AI models for various applications.

Salary

Competitive compensation; Meaningful equity included; Comprehensive benefits and flexible work arrangements

Skills & Requirements

Must-have

  • 5+ years ML research or applied engineering experience
  • Expertise in diffusion models and generative architectures
  • Deep understanding of deep learning optimization fundamentals
  • Experience training large-scale models on GPUs/TPUs
  • Strong proficiency in PyTorch or JAX frameworks
  • Ability to translate research prototypes to production

Nice-to-have

  • Publications in top-tier AI conferences like NeurIPS
  • Experience with large-scale distributed training systems
  • Background in multimodal generation tasks
  • Familiarity with transformer architectures and hybrids
  • Contributions to open-source generative model projects
  • Experience scaling models to billions of parameters

Key Requirements

  • 5+ years of experience in ML research or applied ML engineering
  • Proven experience training large-scale models on GPUs/TPUs
  • Strong mathematical foundation in probability, statistics, and optimization

Work Rights

Not specified

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