Senior Applied Scientist

Adobe • San Jose, CA

9d

About The Position

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 design and deliver exceptional digital experiences! We’re passionate about empowering people to create 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 creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from anywhere in the organization, and we know the next big idea could be yours! Adobe Firefly’s Applied Science & Machine Learning (ASML) group is looking for research scientists and engineers focused on post-training, alignment, and distillation of large-scale generative AI models. Our goal is to push the frontier of generative AI while ensuring models are safe, efficient, aligned with user intent, and deployable at scale. We are particularly interested in candidates with expertise in reinforcement learning from human feedback (RLHF), direct preference optimization (DPO/GRPO), supervised fine-tuning (SFT), and model distillation / efficiency methods. This work directly impacts the quality, efficiency, and safety of Firefly’s image and video generation models, enabling 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 post-training stack, collaborate across data, modeling, and product, and see your work ship to customers worldwide.

Requirements

• Master’s or Ph.D. in Computer Science, Machine Learning, or a related field.
• Strong hands-on experience with large-scale generative AI training and post-training (SFT, RLHF, DPO/GRPO, distillation).
• Familiarity with diffusion models, transformers, or other state-of-the-art 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
• Good publication record in Computer Science, AI/ML or related fields

Responsibilities

• Conduct innovative research and development in post-training alignment and model distillation for large-scale generative AI models.
• Design and evaluate techniques such as RLHF, DPO/GRPO, SFT, reward modeling, and preference optimization to improve instruction-following, controllability, and safety.
• Develop efficient distillation, compression, and inference acceleration methods to make frontier models deployable at scale.
• Collaborate with researchers, engineers, and product teams to transfer post-training innovations into Adobe products.
• Build and maintain pipelines to evaluate generative models across quality, efficiency, and safety metrics.
• Convert research ideas/papers into production-ready implementations in Python and modern ML toolkits.
• Provide technical mentorship and guidance to peers and junior researchers.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees