Lead GenAI Systems & Data Architect

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The Training Data Ecosystem for Generative AI (a.k.a AI-Platform) team at Adobe Firefly is looking for a lead architect to spearhead the design of our GenAi training data ecosystem as well as inference and training code bases. We are looking for proven experience in architecting and building large-scale distributed platforms and a strong background in GenAi / ML, data engineering, and large-scale data management. A passion for enabling cutting-edge AI research and product development is also a must.

This role combines both coordination skills across ML projects and hands-on delivery to evolve the training data ecosystem that powers our generative AI models for content synthesis and editing. This role is pivotal in building and scaling the data infrastructure, pipelines, and strategies essential for developing the next generation of creative tools.

As an architect for GenAi systems and data platforms at Adobe, you will be joining an outstanding team. You will have the opportunity to research, develop, and deploy large-scale machine learning solutions to advance the Creativity world through features in Adobe's products, reaching millions of people worldwide!

• Work closely with data scientists, engineers, researchers, and product managers to build AI/ML solutions on the training data ecosystem to deliver a robust, scalable, and efficient data pipelines for the entire training data lifecycle.
• Execute the comprehensive strategy for acquiring, processing, curating, annotating, versioning, and ensuring the quality of large-scale training datasets for Adobe Firefly.
• Work across organizational boundaries to align priorities and drive projects forward.
• Evaluate and integrate new tools, technologies, and methodologies to continuously improve the training data infrastructure, workflows, and team productivity.

Core Qualifications:

• Masters or Ph.D. in Computer Science, Data Science, Engineering, AI/ML, or a related technical field.
• Proficient in Python and PyTorch.
• Proven ability in building, deploying, measuring, and maintaining large-scale generative models (e.g., GANs, diffusion models, Transformers).
• Proven ability in building large-scale distributed ML pipelines focusing on Generative Ai.
• In-depth knowledge of machine learning algorithms and their applications to business problems with focus on Generative AI specially image and video.
• Deep understanding of the end-to-end data lifecycle for machine learning, particularly the unique challenges and requirements for training large-scale generative models (e.g., GANs, diffusion models).
• Proficiency with cloud-based data storage and processing technologies (e.g., AWS S3/Glue/EMR, Azure Blob Storage/Data Factory, GCP Cloud Storage/Dataflow, Spark, Databricks, Snowflake).

Preferred Experience:

• Experience in full-stack development covering both frontend (UI/UX) and backend as well as familiarity with API design, RESTful services, CI/CD pipelines.
• Experience with MLOps principles and tools, particularly those focused on data management, data versioning (e.g., DVC), and experiment tracking for ML.
• A track record of contributions to open-source data tools, relevant academic publications, or patents in the data management space.
• Experience supporting large-scale generative model training through the delivery of robust and high-quality data solutions.
• Expertise in data quality assessment methodologies, data governance frameworks, data versioning strategies, and data annotation/labeling techniques and platforms.
• Experience working directly with, and managing, large-scale image and/or video datasets, including their acquisition, processing, and quality control.

#FireflyGenAI

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

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Massachusetts:

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