Senior Manager, Applied Science

Adobe
3 Locations$247k – $358kPosted 7 April 2026

Job Description

The Opportunity Adobe Firefly Foundry is a managed generative-AI service purpose-built for enterprises that need to scale content creation without compromising brand safety or workflow efficiency. By letting customers train private Firefly models on their own intellectual property—under strict data isolation and copyright indemnification—and deploy those models directly into Adobe Creative Cloud, Experience Cloud, and proprietary platforms via Firefly Services APIs, Firefly Foundry closes the gap left by consumer‑grade GenAI tools and empowers brands to deliver ten‑times the creative output at professional quality. As a Manager for Applied Research at Adobe, you will be the technical and strategic steward of this platform, translating pioneering research into secure, production‑ready capabilities, championing them in customer and industry settings, and building the world‑class team that will turn vision into reality. Responsibilities: Lead and grow a distributed team focused on Generative AI. Define and execute strategy for acquiring, processing, curating, annotating, versioning, and ensuring quality of large-scale datasets to support diverse customer use cases. Enable novel capabilities for controllable and precise multi-modal content generation with Generative AI, solving real customer problems. Build and maintain scalable, efficient data, pre-training, and post-training pipelines across the ML model lifecycle. Collaborate with researchers, ML engineers, and PMs to align on data, architecture, and control needs for new models. Evaluate and integrate tools and methodologies to enhance infrastructure and workflows. Champion data diversity, bias mitigation, and ethical AI practices. Provide technical leadership and foster a culture of innovation. Partner across teams to align priorities and share best practices. Qualifications: Ph.D. in CS, Data Science, Engineering, AI/ML, or related field—or equivalent experience. 10 years in engineering and research leadership, managing full lifecycle of ML models from research to direct impact on customer workflows. Deep understanding of ML data lifecycles, especially for modern generative models. Expertise in data quality, governance, versioning, and annotation platforms. Proficiency with cloud tech (AWS, Azure, GCP, Spark, Databricks, Snowflake). Strong grasp of data privacy, security, and ethical AI principles. Excellent leadership and cross-functional collaboration skills. Experience with large-scale image/video datasets and training generative models. Preferred: Experience with computer graphics and VFX pipelines. Experience in computer vision, multimedia, or creative content ecosystems. Contributions to open-source tools, publications, or patents in computer vision, machine learning, and computer graphics. Proven success supporting at-scale generative model training #FireflyGenAI About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000 employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the s ... (truncated, view full listing at source)
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