Manager, Applied Science

Adobe

Applied Science Manager leading and evolving training data ecosystem for Adobe’s generative AI models. Collaborating with teams to define data strategies and quality assurance.

Posted 6/19/2026full-timeSan Jose • California, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $172,500 - $306,625 per yearWebsite

About the role

Key responsibilities & impact

Lead and grow a distributed team focused on training data for generative AI.
Define and execute the strategy for acquiring, processing, curating, annotating, versioning, and ensuring the quality of large-scale datasets for Custom Foundation Models.
Build and maintain scalable, efficient data pipelines across the training data lifecycle.
Collaborate with researchers, ML engineers, and product managers to align on data needs for foundation models.
Champion data diversity, bias mitigation, and ethical AI practices.
Evaluate and integrate tools and methodologies that enhance infrastructure and workflows.
Influence model development through insights on data quality and availability.
Provide technical leadership and foster a culture of innovation.
Partner across teams to align data priorities and share best practices.

Requirements

What you’ll need

Master’s or Ph.D. in Computer Science, Data Science, Engineering, AI/ML, or a related field — or equivalent experience.
5+ years of experience in engineering leadership.
Deep understanding of ML data lifecycles, particularly for generative models.
Experience in the science and algorithms underpinning data for generative AI.
Experience with synthetic data creation and curation.
Strong grasp of data privacy, security, and ethical AI principles.
Excellent leadership and cross-functional collaboration skills.
Experience working with large-scale image and video datasets.

Benefits

Comp & perks

Health insurance
401k matching
Flexible work hours
Paid time off
Professional development opportunities

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data pipelinesdata processingdata curationdata annotationdata versioningdata qualitygenerative AIsynthetic data creationmachine learning (ML)data lifecycles

Soft Skills

leadershipcross-functional collaborationinnovationcommunicationstrategic thinkinginfluencechampioning diversitybias mitigationethical AI practicesteam building

Certifications

Master’s degreePh.D.