Currently tracking 218 active AI roles, down 50% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $114k–$397k (avg $221k).
Adobe has 306 active job listings related to artificial intelligence. The majority of these roles, 47%, are focused on agents, with application-focused roles making up another 25%. Engineering is the primary function for these positions, with the United States being the dominant hiring country. Frequent technical tags include model serving, agent orchestration, and fine-tuning, suggesting a focus on deploying and managing AI models.
Adobe currently has 314 active AI-related roles in our index. The most common open titles are: Senior Software Development Engineer (12), Machine Learning Engineer (6), Machine Learning Engineer 4 (5), Principal Product Manager (5), Software Development Engineer (5). Most positions are in Engineering and Product.
Adobe's active AI hiring is concentrated in: agents (48%), application (25%), serving infrastructure (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Adobe is hiring AI talent in: United States (236 roles), India (50 roles), Romania (22 roles), Canada (3 roles).
Job postings at Adobe most frequently reference: model serving, agent orchestration, llm observability, fine tuning, inference infra.
In the past 30 days, Adobe has posted 119 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Sr Applied Scientist, Generative AI/ML This role focuses on conducting research and development in Generative AI for visual, audio, and multi-modal outputs, with a strong emphasis on preparing data, training, fine-tuning, and adapting large foundation models. The scientist will develop and deploy novel generative AI technologies into Adobe products, publish research, and collaborate with other researchers and ML engineers. | Post-trainPretrain | 9 |
| Staff Applied Scientist, Generative AI/ML Staff Applied Scientist role focused on Generative AI research and development for visual, audio, and multi-modal outputs. The role involves pioneering research, developing novel generative AI technologies, and training/fine-tuning large foundation models across various modalities. Emphasis on publishing research and collaborating with ML engineers to integrate technologies into Adobe products. |
| Post-trainPretrain |
| 9 |
| Senior Staff Applied Scientist - AI/ML Senior Staff Applied Scientist role at Adobe focusing on transforming AI/ML research breakthroughs into innovative product features for Generative AI, LLMs, and multimodal AI. The role involves scouting, adapting, and improvising research, prototyping, rapid experimentation, and deploying practical innovations for Adobe's products. Responsibilities include developing and enhancing GPU-accelerated pipelines for model training and inference, collaborating with researchers and ML engineers, and publishing work. Requires a Ph.D. or Masters with 10+ years of experience in AI/ML, with expertise in training AI/ML models in multimodal LLMs, Image, or Video, proficiency in training and optimizing large-scale models, and experience with post-training techniques like fine-tuning and alignment. | Post-trainServe | 9 |
| Applied Scientist Research Scientist role focused on training large-scale generative AI models for image and video synthesis, emphasizing conditional generation, editing, and improving instruction compliance, controllability, and visual clarity. The role involves collaborating cross-functionally, developing evaluation pipelines, and translating research into production-ready implementations. | Post-trainPretrain | 9 |
| Senior Research Scientist Senior Research Scientist at Adobe Speech AI Lab focusing on speech generative AI, audio modeling, and multimodal learning. The role involves leading independent research, designing and advancing state-of-the-art AI models and training procedures, including foundation models and generative systems. Emphasis on modern large-scale model architectures, publishing research, and building prototypes for product integration. | Post-trainPretrain | 9 |
| Applied Scientist, Generative AI/ML Research scientist role focused on generative AI for visual, audio, and multi-modal outputs. Involves pioneering research, development, and deployment of novel generative AI technologies, including large-scale foundation models with deep reasoning capabilities. Requires expertise in training and fine-tuning models across various modalities and proficiency in deep learning frameworks. | Post-trainPretrain | 9 |
| 2026 University Graduate - Research Scientist/Engineer Research Scientist role focused on developing new music generation technology using generative AI, sequence modeling, multi-modal modeling, reinforcement learning, LLMs, diffusion, and distillation techniques. The goal is to push the state of the art and productize research for real-world impact in music creation. | Post-trainPretrain | 9 |
| Applied Scientist Applied Scientist role focused on developing and fine-tuning large-scale foundation models for video understanding and generation, leveraging state-of-the-art Generative AI technologies. The role involves converting research ideas into production-ready code and collaborating with researchers and engineers. | Post-trainServe | 8 |
| Research Scientist/Engineer - Photoshop Research Scientist/Engineer at Adobe focused on image generation/restoration, low-level vision, and image editing for Photoshop, with an eventual posture toward productization. Requires expertise in AI, ML, computer vision, and image processing, with a preference for experience in light transport, image formation, or physically based rendering, and leveraging synthetic 3D scene data. | Post-trainData | 8 |
| Senior Machine Learning Engineer Senior Machine Learning Engineer at Adobe Journey Optimizer B2B, focusing on AI-powered customer journey orchestration. The role involves training and fine-tuning ML models, architecting ML pipelines, and contributing to the deployment and production operations of ML models and systems. Experience with generative AI, LLMs, fine-tuning, and MLOps is required, with a preference for RAG, agentic workflows, and personalization use cases. | Post-trainAgent | 8 |
| Sr. Applied Scientist Sr. Applied Scientist at Adobe focused on improving the quality and controllability of generative multimodal models, specifically in mid-training capabilities for image and video editing. The role involves designing and implementing training pipelines, identifying quality gaps, developing data curation and distributed training workflows, and optimizing inference for production environments. | Post-trainData | 8 |
| Applied Scientist Applied Scientist at Adobe focused on transforming research breakthroughs in Generative AI, LLMs, and multimodal AI into innovative product features for millions of users. The role involves scouting, adapting, and improvising the latest research, prototyping, and deploying practical innovations, with a strong emphasis on training and optimizing large-scale models, including post-training techniques and GPU-accelerated pipelines for both training and inference. | Post-trainServe | 8 |
| 2026 AI/ML Intern - Machine Learning Engineer/Researcher Intern Internship opportunity within Adobe Firefly's applied research organization focusing on AI and generative technologies. The role involves pioneering data, models, applications, and scientific evaluation for images, videos, language, and multimodal models, contributing to both research and product development. | Post-trainServe | 8 |
| Senior Applied Scientist Senior Applied Scientist role at Adobe focused on post-training and distillation of large generative AI models (images and videos) to improve quality, efficiency, and deployability. The role involves developing and refining pipelines like SFT, preference optimization, and model distillation, as well as building infrastructure for these processes and optimizing models for deployment. Collaboration with research, data, and infrastructure teams is key. | Post-trainServe | 7 |
| Applied Scientist 3 This role focuses on post-training and distillation of large generative AI models for images and videos, aiming to improve quality, efficiency, and deployability. Responsibilities include developing distillation pipelines, refining post-training methods (SFT, DPO, GRPO, reward-based learning), building infrastructure for training workflows, and optimizing models for deployment efficiency. The role collaborates with researchers and engineers to adapt complex models into efficient production versions. | Post-trainServe | 7 |