Adobe

This role leads a distributed team focused on Generative AI for Adobe Firefly Foundry, an enterprise-grade managed service. Responsibilities include defining strategy for data acquisition, processing, and quality, enabling multi-modal content generation, and building scalable data, pre-training, and post-training pipelines. The role requires deep understanding of ML data lifecycles, expertise in data quality and governance, and proficiency with cloud technologies, with a focus on ethical AI practices and leading a team through the full ML model lifecycle from research to customer impact.

Director to lead Multimodal Data Research organization responsible for scaling, quality, and innovation in multimodal training data (image, video, audio) for Adobe Firefly's foundational generative and editing models. The role involves setting vision, leading multiple senior teams, and orchestrating execution across data ingestion, filtering, captioning, generation, editing-centric datasets, and data-driven training experiments.

Manager for a team building core systems that support training and development of foundation models for generative AI (image, video, multimodal). Focus on foundational training frameworks, tooling, and codebases for large-scale experimentation, reliable execution, and rapid iteration. Requires strong software engineering, systems experience, and applied ML understanding.

Machine Learning Data Engineer at Adobe focused on building foundational infrastructure for large-scale multimodal AI training and inference. The role involves developing distributed data loaders, feature enrichment pipelines, and dataset management systems to support foundation model training at petabyte scale, processing billions of multimodal assets.

This role is for a Manager of Applied Research focused on leading and growing a team responsible for training data for Adobe's enterprise generative AI service, Firefly Foundry. The responsibilities include defining and executing strategy for acquiring, processing, curating, annotating, versioning, and ensuring the quality of large-scale datasets, building scalable data pipelines, and collaborating with researchers and ML engineers. The role requires strong leadership, deep understanding of ML data lifecycles for generative models, and expertise in cloud data technologies.

Director of Machine Learning Engineering to lead a team in evolving a data platform to support AI/ML innovation, focusing on big-data management and compute abstractions within a governed trust framework.