Applied Scientist - Multimodal

Adobe

Multiple Locations
$142,700 -- $270,950 annually; not specified; not ...
Generative ai research
Multimodal reasoning
Large-scale inference systems
The Adobe Firefly Applied Science & Machine Learning team is building next-generation multimodal guardrail systems for building safe and compliant image, video, and audio generative models powering Firefly.com

Job Summary

  • The Adobe Firefly Applied Science & Machine Learning team is building next-generation multimodal guardrail systems for building safe and compliant image, video, and audio generative models powering Firefly.com.
  • This role sits at the intersection of generative model alignment, multimodal reasoning, and large-scale inference systems, driving research in inference-time alignment, rapid scientific experimentation, vision-language reasoning, and multimodal IP-aware generative modeling.
  • Collaborate with research scientists, ML engineers, applied ethics, and legal teams to translate scientific advances into deployed systems and contribute to the broader research strategy around generative AI alignment and safety within Adobe.

Matching Summary

The Adobe Firefly Applied Science & Machine Learning team is building next-generation multimodal guardrail systems for building safe and compliant image, video, and audio generative models powering Firefly.com.

Salary

$142,700 -- $270,950 annually; Not specified; Not specified

Skills & Requirements

Must-have

  • Generative AI research
  • Multimodal reasoning
  • Large-scale inference systems
  • Model alignment strategies
  • Vision-Language Models
  • Python and PyTorch

Nice-to-have

  • AI-assisted development workflows
  • Cross-functional collaboration
  • Research publications
  • Safety evaluation frameworks

Key Requirements

  • PhD or MS in Computer Science, Machine Learning, AI, or related field
  • 5+ years of experience in applied ML or generative AI research
  • Strong background in large-scale generative models
  • Deep experience with model fine-tuning
  • Expertise in Vision-Language Models
  • Proficiency in Python and modern ML frameworks
  • Strong experimental development and statistical evaluation skills
  • Experience analyzing complex failure modes
  • Understanding of large-scale inference systems
  • Ability to navigate open-ended research spaces

Work Rights

Not specified

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