Senior Applied Scientist

Adobe • San Jose, CA

2d • $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