Senior Applied Scientist

Adobe • San Jose, CA

1d • $164,000 - $313,300

About The Position

About the Role: This role targets an elevated profile to handle high-visibility projects and build foundational capabilities. You will be expected to materially improve the quality and controllability of Adobe’s generative multimodal models. By strengthening Adobe’s competitive position in generative AI quality and alignment, you will drive sustained improvements.

Requirements

• Ph.D. in Computer Science, Machine Learning, or a related field preferred.
• Proven track record in pre-training of large-scale multimodal models, specifically on cross modality for image and video data.
• Deep understanding of pre-training for multimodal generative models.
• Strong expertise in Vision-Language Models (VLMs), including experience with contrastive learning, multimodal alignment, and leveraging VLM-based encoders to improve semantic understanding in generative tasks.
• Deep understanding of modern diffusion-based architectures (DiT).
• Ability to design and implement scalable pipelines for data curation, data quality control, and distributed training in collaboration with data and infrastructure teams.
• Experience optimizing model inference and deployment for high-throughput product environments, ensuring a balance between generative quality and computational efficiency.
• Since this is junior role, we need the role has strong publications experience and previous industry level intern experience.

Responsibilities

• Design and implement end-to-end training pipelines to build foundational model for both images and videos.
• Lead core development for specific pre-training areas (e.g., text to image and text to video), while aligning with broader team strategy.
• Develop scalable workflows for data curation, data quality improvements, and distributed training.
• Partner closely with research, data, evaluation, infrastructure, pre-training and post-training teams to push the editing quality for both images and videos.
• Closely collaborate with both pre-training and post-training team to understand the model’s capability and limitations to propose actionable solutions to improve quality.
• Improve instruction-following, visual fidelity, and edit consistency through higher quality data and better training recipes.

What This Job Offers

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