$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