Senior Applied Scientist - AI​/ML

Our Company

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 everywhere in the organization, and we know the next big idea could be yours!

Adobe is seeking Senior Staff Applied Scientists who excel at turning research breakthroughs into innovative product features. In this role, you will focus on scouting, adapting, and improvising the latest research to advance Adobe’s AI capabilities in the field of Natural Language, Image/Video generation, editing, and multimodal AI that impact millions of users. We welcome outstanding candidates in all related technical fields, such as Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing, Large language models.

Familiarity with inference optimization, performance trade-offs, and scalable integration will be an asset. We are looking for a candidate who is motivated by moving fast with research and innovation and wants their ideas to shape the future of Adobe products.

• Transform innovative research concepts into practical applications within the realm of Generative AI, LLMs, Reinforcement learning, Reasoning, Evaluations.
• Prototype and experiment rapidly, demonstrating feasibility and business impact.
• Push beyond academic results to develop and deploy practical, differentiated innovations for Adobe’s products.
• Collaborate with world‑class researchers and ML engineers to bring research ideas to production.
• Publish and present your work in world‑class scientific venues in AI/ML fields.
• Develop and enhance GPU‑accelerated pipelines for (customized) model training and inference, focusing on performance, scalability, and reliability.
• Foster a culture of innovation, technical excellence, and continuous improvement across the organization.

• Ph.D. or Masters or equivalent experience in Engineering, Computer Science, AI/ML or related fields and 10+ professional experience.
• Research or industry experience in training AI/ML models in at least one of the following modalities: multimodal LLMs, Image, Video.
• Proficiency in training and optimizing large‑scale models, involving data curation, distributed training, and memory‑efficient strategies.
• Experience with post‑training techniques such as fine‑tuning, alignment or distillation.
• Proficiency with modern deep learning frameworks (e.g., PyTorch) and experience scaling models on GPU/TPU clusters.
• Excellent communication skills and a strong great teammate.

• Experience on large‑scale generative model training.
• Experience on synthetic data generation.
• Previous involvement with product teams in technology transfers.
• Experience of working with large‑scale datasets.

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $182,900 – $334,500 annually. Pay within this range varies by work location and may also depend on job‑related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short‑term incentives are in the form of sales commission plans. Non‑sales roles starting salaries are expressed as base salary and short‑term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long‑term incentives in the form of a new hire equity award.

California:

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