Applied Scientist

Adobe Adobe · Enterprise · Seattle, WA +1

The Applied Scientist will work on post-training and distillation of large generative AI models for Adobe Firefly, focusing on improving quality, efficiency, and scalability for image and video generation. Responsibilities include developing distillation pipelines, applying post-training methods like SFT and preference optimization, building tools for data and training workflows, and optimizing models for deployment.

What you'd actually do

  1. Develop and run distillation pipelines to transfer capabilities from large teacher models to efficient student models
  2. Apply and improve post-training methods, including supervised fine-tuning (SFT), preference optimization (DPO/GRPO), and reward-based learning
  3. Build tools and infrastructure for teacher rollout generation, data pipelines, and training workflows
  4. Design and run experiments to improve model quality, efficiency, and instruction alignment
  5. Partner with research scientists to translate ideas into scalable pipelines and production-ready systems

Skills

Required

  • MS or PhD in Computer Science or a related field
  • Experience with machine learning algorithms and model distillation techniques
  • Strong programming skills in Python or similar languages
  • Experience training and optimizing AI models

Nice to have

  • Experience with large-scale data pipelines
  • Familiarity with Adobe products

What the JD emphasized

  • refine and compress large-scale AI models
  • improve the quality, efficiency, and scalability of generative models for images and video
  • adapt large, complex models into efficient production systems
  • bring post-training improvements into production

Other signals

  • refine and compress large-scale AI models
  • improve the quality, efficiency, and scalability of generative models for images and video
  • adapt large, complex models into efficient production systems
  • bring post-training improvements into production