Applied Scientist 3

Adobe Adobe · Enterprise · San Jose, CA

Research Scientist role focused on large-scale pre-training and mid-training of multi-modality generative AI models for image and video synthesis, with an emphasis on improving instruction compliance, controllability, and visual clarity. The role involves conducting innovative research, developing sophisticated techniques, collaborating cross-functionally, and translating research into production-ready implementations for Adobe's creative products.

What you'd actually do

  1. Conduct innovative research and development in training large-scale generative AI models for image and video synthesis.
  2. Develop, carry out, and carefully assess sophisticated techniques for conditional generation and editing. Emphasize improving instruction compliance, controllability, and visual clarity in pre-trained image and video models.
  3. Collaborate cross-functionally with researchers, engineers, and product teams to translate multimodal innovations into scalable downstream applications coordinated within Adobe products.
  4. Develop and maintain robust evaluation pipelines to assess generative models across quality, efficiency, robustness, and safety metrics.
  5. Translate research concepts and published work into production-ready implementations using Python and modern machine learning frameworks.

Skills

Required

  • Master’s or Ph.D. degree in Computer Science, Machine Learning, or a related field
  • Extensive practical experience in large-scale generative AI training concentrating on image and video generation and editing
  • Familiarity with diffusion models, transformers, or other brand new generative architectures
  • Excellent communication skills
  • Ability to collaborate across cross-functional teams
  • Strong coding and prototyping ability in Python, PyTorch, and ML infrastructure tools
  • Working with product teams on technology transfers
  • Strong history of publishing in Computer Science, AI/ML, or related areas

Nice to have

  • conditional generation
  • editing of large generative AI models
  • image and video synthesis
  • instruction compliance
  • controllability
  • visual clarity
  • pre-trained image and video models
  • multimodal innovations
  • evaluation pipelines
  • quality
  • efficiency
  • robustness
  • safety metrics
  • research concepts
  • published work
  • production-ready implementations

What the JD emphasized

  • large-scale, industry-level pre-training
  • mid-training
  • multi-modality generative models
  • image and video generation
  • image and video synthesis
  • instruction compliance
  • controllability
  • visual clarity
  • pre-trained image and video models
  • multimodal innovations
  • evaluation pipelines
  • quality
  • efficiency
  • robustness
  • safety metrics
  • research concepts
  • published work
  • production-ready implementations
  • Master’s or Ph.D. degree
  • extensive practical experience
  • large-scale generative AI training
  • image and video generation and editing
  • diffusion models
  • transformers
  • brand new generative architectures
  • Strong coding and prototyping ability
  • Python
  • PyTorch
  • ML infrastructure tools
  • Working with product teams
  • technology transfers
  • Strong history of publishing

Other signals

  • large-scale pre-training
  • multi-modality generative models
  • image and video generation
  • next-generation creative workflows