Staff Applied Scientist

Adobe; San Jose (CA); On-site; USD 164,000 - 313,300; Full time

Job summary

A leading technology company is seeking a qualified candidate for a role focused on enhancing generative AI models. You will design and implement training pipelines, lead development in multimodal areas, and collaborate with various teams to improve quality and efficiency. A Ph.D. in a relevant field is preferred, along with a strong publication record and industry internship experience. The position offers a competitive salary range in California of $216,400–$313,300 annually.

Qualifications

• Strong publications experience in multimodal generative models.
• Previous industry-level internship experience is required.
• Deep understanding of pre-training for multimodal generative models.

Responsibilities

• Design and implement training pipelines for models.
• Lead development for pre-training areas for text to image and video.
• Develop scalable workflows for data quality improvements.

Skills

Pre-training of large-scale multimodal models

Vision-Language Models (VLMs)

Data curation

Distributed training

Education

Ph.D. in Computer Science, Machine Learning, or related field

Tools

Modern diffusion-based architectures (DiT)

Job description

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.

Key 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 teams to understand the model’s capability and limitations and propose actionable solutions to improve quality.
• Improve instruction-following, visual fidelity, and edit consistency through higher quality data and better training recipes.

Qualifications & 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.
• For this junior role, strong publications experience and previous industry‑level internship experience is required.

Pay Range

The U.S. pay range for this position is $164,000 – $313,300 annually. In California, the pay range is $216,400 – $313,300.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic.