Adobe Systems

4 weeks ago

Staff Applied Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Join Adobe Firefly’s ASML group to advance multimodal generative AI by leading mid-training and editing pipelines for image, video, and audio. You will shape architectural decisions, drive data curation and distributed training, mentor engineers, and collaborate with research, data, and product teams to ship high-quality, scalable AI models globally.

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Define and drive the technical strategy for mid-training approaches that improve editing capabilities across Adobe's multimodal generative models for image, video, and audio.
•Own and drive multiple complex workstreams within the mid-training stack (e.g., image-to-image editing, instruction-based editing, cross-modal editing), making key architectural and prioritization decisions.
•Set technical direction for large-scale captioning pipelines and lead VLM finetuning strategy to improve multimodal understanding across visual and auditory domains.
•Own end-to-end workflows for data curation, quality improvements, and distributed training, driving infrastructure decisions that unblock the broader organization.
•Drive alignment across research, data, evaluation, infrastructure, pre-training, and post-training teams, influencing leadership on technical strategy and investment priorities.

Key Requirements

•Ph.D. in Computer Science, Machine Learning, or a related field, with significant industry experience building and shipping large-scale ML systems.
•Deep expertise in modern generative architectures such as diffusion models, with experience owning end-to-end conditional generation or editing pipelines for image, video, or audio.
•Proven ability to architect and scale ML systems using frameworks like PyTorch, including leading distributed training infrastructure design.
•Extensive experience in VLM finetuning for image, video, and audio understanding, with a track record of aligning research goals with product requirements.
•Experience owning large-scale automated captioning pipelines across image, video, and audio datasets.

Experience:Multimodal AIGenerative AIMachine learning

Education:PhD / Doctorate

Skills:PythonPyTorchDistributed trainingMachine learningDeep learningDiffusion modelsImage/video/audio understanding

Languages:English

Tech Stack:PythonPyTorchDiffusion modelsVLMLarge-scale trainingDistributed training

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

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Adobe Systems

4 weeks ago

Staff Applied Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Define and drive the technical strategy for mid-training approaches that improve editing capabilities across Adobe's multimodal generative models for image, video, and audio.
•Own and drive multiple complex workstreams within the mid-training stack (e.g., image-to-image editing, instruction-based editing, cross-modal editing), making key architectural and prioritization decisions.
•Set technical direction for large-scale captioning pipelines and lead VLM finetuning strategy to improve multimodal understanding across visual and auditory domains.
•Own end-to-end workflows for data curation, quality improvements, and distributed training, driving infrastructure decisions that unblock the broader organization.
•Drive alignment across research, data, evaluation, infrastructure, pre-training, and post-training teams, influencing leadership on technical strategy and investment priorities.

Key Requirements

•Ph.D. in Computer Science, Machine Learning, or a related field, with significant industry experience building and shipping large-scale ML systems.
•Deep expertise in modern generative architectures such as diffusion models, with experience owning end-to-end conditional generation or editing pipelines for image, video, or audio.
•Proven ability to architect and scale ML systems using frameworks like PyTorch, including leading distributed training infrastructure design.
•Extensive experience in VLM finetuning for image, video, and audio understanding, with a track record of aligning research goals with product requirements.
•Experience owning large-scale automated captioning pipelines across image, video, and audio datasets.

Experience:Multimodal AIGenerative AIMachine learning

Education:PhD / Doctorate

Skills:PythonPyTorchDistributed trainingMachine learningDeep learningDiffusion modelsImage/video/audio understanding

Languages:English

Tech Stack:PythonPyTorchDiffusion modelsVLMLarge-scale trainingDistributed training

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