Principal Applied Researcher

Adobe Adobe · Enterprise · San Jose, CA +1

Applied Researcher role focused on building innovative machine learning models for Agentic and Generative AI scenarios within Adobe Express. The role involves developing and deploying advanced ML models in computer vision, NLP, and multimodal learning, contributing to foundational AI systems for creative workflows, and designing evaluation strategies. Requires experience with modern ML architectures, cloud platforms, MLOps, and deploying ML systems at scale, with a preference for experience with LLMs and agent-based systems.

What you'd actually do

  1. Build innovative machine learning models that drive Agentic and other Generative AI scenarios for Adobe Express.
  2. Develop and deploy advanced ML models in areas such as computer vision, NLP, and multimodal learning.
  3. Contribute to foundational AI systems for intelligent assistance, layout automation, image generation, and motion storytelling.
  4. Design and build modular ML components that integrate into Adobe’s Horizon AI Stack and serve multiple creative workflows.
  5. Drive the end-to-end ML lifecycle—from experimentation to evaluation, optimization, and production deployment.

Skills

Required

  • Masters or PhD in Computer Science, Computer Engineering, Data Science, Machine Learning, or related field with equivalent experience
  • Strong programming skills
  • Proficiency in ML frameworks such as PyTorch, TensorFlow, or JAX
  • Experience with modern ML architectures including transformers / visual transformers, diffusion models, or GANs
  • Experience with cloud platforms, MLOps and deploying ML systems in production at scale
  • Ability to quickly read, understand and prototype relevant research papers

Nice to have

  • Experience with Large Language Models and model adaptation techniques (Ex: PEFT, SFT, RL etc.)
  • Familiarity with agent-based systems, intelligent assistants, or planner-based AI
  • Experience in creative, imaging, or multimedia domains
  • Publications in renowned ML/CV/AI conferences (e.g., NeurIPS, CVPR, ICML, SIGGRAPH)

What the JD emphasized

  • Masters, or PhD (preferred) in Computer Science, Computer Engineering, Data Science, Machine Learning, or a related field with equivalent experience.
  • Experience with modern ML architectures including transformers / visual transformers, diffusion models, or GANs.
  • Experience with cloud platforms, MLOps and deploying ML systems in production at scale.
  • Be able to quickly read, understand and prototype relevant research papers.
  • Experience with Large Language Models and model adaptation techniques (Ex: PEFT, SFT, RL etc.)
  • Familiarity with agent-based systems, intelligent assistants, or planner-based AI.
  • Publications in renowned ML/CV/AI conferences (e.g., NeurIPS, CVPR, ICML, SIGGRAPH).

Other signals

  • develop and deploy advanced ML models
  • design and build modular ML components
  • drive the end-to-end ML lifecycle
  • design evaluation strategies