Adobe Systems

3 weeks ago

Applied Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Join Adobe Firefly’s ASML group to advance conditional generation and editing for large multimodal generative models focused on images and videos. You’ll design and evaluate mid-training approaches, own components in the training stack, and run experiments to improve editing quality. Build scalable captioning pipelines, support VLM finetuning, and contribute to data curation, quality improvements, and distributed training workflows—collaborating across research, modeling, data, evaluation, and infrastructure.

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Contribute to the design, implementation, and evaluation of mid-training approaches that improve editing capabilities for multimodal generative models across image, video, and audio.
•Own components within the mid-training stack (e.g., image-to-image editing or instruction-based editing) by designing and running experiments to test hypotheses and identify quality gaps.
•Build and maintain large-scale captioning pipelines and support VLM finetuning efforts to improve multimodal understanding across visual and auditory domains.
•Assist in building scalable workflows for data curation, quality improvements, and distributed training, applying research insights from diffusion models and large-scale training to practical model improvement.
•Collaborate with research, data, evaluation, infrastructure, pre-training, and post-training teams, and document experiments, datasets, and training approaches.

Pay and Benefits

Salary: USD 120,700 - 238,600 annually

Key Requirements

•Possession of a Master’s or Ph.D. degree in Computer Science, Machine Learning, or a related field.
•Solid understanding of modern generative architectures such as diffusion models, with familiarity with conditional generation or editing methods for image, video, or audio.
•Experience implementing machine learning models using modern deep learning frameworks (e.g., PyTorch), with exposure to large-scale or distributed training workflows.
•Experience or research background in VLM finetuning focused on image, video, and audio understanding, including adapting pretrained vision-language models for downstream multimodal tasks.
•Familiarity with captioning for large-scale data, including designing or applying automated captioning pipelines for image, video, and audio datasets.

Education:Master's in Computer Science, Machine Learning

Skills:CommunicationCollaborationResearch skills

Tech Stack:PythonPyTorchDiffusion modelsVLM finetuningVision-language modelsCaptioningMultimodal generative models

Company Brief

Adobe Systems

Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1982

Glassdoor: 4.0

Website LinkedIn Glassdoor

Loading job details...

Preparing the role view and application actions.

Adobe Systems

3 weeks ago

Applied Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Contribute to the design, implementation, and evaluation of mid-training approaches that improve editing capabilities for multimodal generative models across image, video, and audio.
•Own components within the mid-training stack (e.g., image-to-image editing or instruction-based editing) by designing and running experiments to test hypotheses and identify quality gaps.
•Build and maintain large-scale captioning pipelines and support VLM finetuning efforts to improve multimodal understanding across visual and auditory domains.
•Assist in building scalable workflows for data curation, quality improvements, and distributed training, applying research insights from diffusion models and large-scale training to practical model improvement.
•Collaborate with research, data, evaluation, infrastructure, pre-training, and post-training teams, and document experiments, datasets, and training approaches.

Pay and Benefits

Salary: USD 120,700 - 238,600 annually

Key Requirements

•Possession of a Master’s or Ph.D. degree in Computer Science, Machine Learning, or a related field.
•Solid understanding of modern generative architectures such as diffusion models, with familiarity with conditional generation or editing methods for image, video, or audio.
•Experience implementing machine learning models using modern deep learning frameworks (e.g., PyTorch), with exposure to large-scale or distributed training workflows.
•Experience or research background in VLM finetuning focused on image, video, and audio understanding, including adapting pretrained vision-language models for downstream multimodal tasks.
•Familiarity with captioning for large-scale data, including designing or applying automated captioning pipelines for image, video, and audio datasets.

Education:Master's in Computer Science, Machine Learning

Skills:CommunicationCollaborationResearch skills

Tech Stack:PythonPyTorchDiffusion modelsVLM finetuningVision-language modelsCaptioningMultimodal generative models

Company Brief

Adobe Systems

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 1982

Glassdoor: 4.0

Website LinkedIn Glassdoor