Senior Applied Scientist

Adobe
San Francisco$187k – $271kPosted 7 April 2026

Job Description

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to build and deliver outstanding digital experiences! We’re passionate about empowering people to develop beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to crafting outstanding employee experiences. Everyone is respected and has access to equal opportunity. We realize new ideas can come from anywhere in the organization. We know the next big idea could be yours! Adobe Firefly’s Applied Science & Machine Learning (ASML) group is seeking research scientists and engineers passionate about conditional generation and editing of large-scale generative AI models. They will concentrate on images and videos. Our aim is to advance generative AI and ensure models have high quality and controllability. We are especially seeking candidates experienced in large-scale, industry-grade pre-training and mid-training of multi-modality generative models. This role directly influences the quality of Adobe’s image and video generation models, supporting next-generation creative workflows for millions of users. As an Applied Scientist at Adobe, you will join a world-class team of applied researchers and engineers building the future of digital experiences. You will have the opportunity to innovate across the full training stack, collaborate across data, modeling, and product, and see your work ship to customers worldwide. Job Responsibilities Conduct innovative research and development in training large-scale generative AI models for image and video synthesis. Develop, carry out, and carefully evaluate sophisticated techniques for conditional generation and editing. This work emphasizes improving instruction adherence, controllability, and the visual quality of pre-trained image and video models. Collaborate cross-functionally with researchers, engineers, and product teams to translate multimodal innovations into scalable downstream applications coordinated within Adobe products. Define and build comprehensive evaluation frameworks and benchmarking pipelines to assess generative models across quality, efficiency, safety, and reliability, establishing guidelines and standards for the organization. Translate research concepts and published work into production-ready implementations using Python and modern machine learning frameworks. Collaborate with technical leads to build long-term technical strategy and roadmap, while mentoring and guiding junior engineers and researchers to elevate team capability and impact. What you'll need to succeed Hold a Master’s or Ph.D. in Computer Science, Machine Learning, or a closely related area. Extensive practical experience in large-scale generative AI training emphasizing the creation and modification of images and videos. Familiarity with diffusion models, transformers, or other brand new generative architectures. Excellent communication skills and ability to collaborate across cross-functional teams. Strong coding and prototyping ability in Python, PyTorch, and ML infrastructure tools. Working with product teams on technology transfers Strong history of publications in Computer Science, AI/ML, or related areas About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000 employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe i ... (truncated, view full listing at source)
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