2026 University Graduate - Applied Scientist

Adobe Adobe · Enterprise · San Jose, CA +1

Research Scientist role focused on Generative AI, specifically preparing data, training, fine-tuning, and adapting large foundation models across various modalities (images, video, 3D, LLMs, cross-modal). The role involves pioneering research and development for visual, audio, and multi-modal outputs, deploying new generative AI technologies into Adobe products, and researching novel large-scale foundation models with deep reasoning capabilities. Collaboration with researchers and ML engineers is expected, along with publishing work in scientific venues.

What you'd actually do

  1. Conduct pioneering research and development in Generative AI for visual (image/video/3D), audio, and multi-modal outputs.
  2. Develop and deploy novel generative AI technologies to existing and new Adobe Products.
  3. Research and develop novel large-scale foundation models with deep reasoning and world-building capabilities.
  4. Collaborate with world-class researchers and ML engineers to bring research ideas to creative workflows used by millions.
  5. Publish and present your work in world-class scientific venues in CV/AI/ML/CG fields

Skills

Required

  • Generative AI
  • training Generative AI models
  • pre-training
  • post-training
  • large-scale model training
  • data curation
  • distributed training
  • memory-efficient techniques
  • fine-tuning
  • alignment
  • distillation
  • PyTorch
  • GPU/TPU clusters

Nice to have

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Natural Language Processing
  • image generation
  • video generation
  • 3D generation
  • audio generation
  • multimodal generation
  • image understanding
  • video understanding
  • 3D understanding
  • audio understanding
  • LLMs
  • cross-modal setups
  • creative workflows

What the JD emphasized

  • PhD or MS degree in CV/AI/ML/CG or related fields 0-2+ years of experience in specific skill/field(s)
  • Research or industry experience in training Generative AI models (pre-training and/or post-training) in at least one of the following modalities: image, video, 3D, or audio.
  • Expertise in large-scale model training and optimization, including data curation, distributed training, and memory-efficient techniques.
  • Experience with post-training techniques such as fine-tuning, alignment or distillation.

Other signals

  • Generative AI
  • foundation models
  • multimodal