Director of Machine Learning

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. 

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity 

We are seeking a highly motivated generative AI training and data leader to head our centralized training and data frameworks that power not research and firefly production at scale. As the Machine Learning leader in AI platform for training and data, you will be responsible for leading and curating a foundational product for training large models with cutting edge optimizations built in. You will also be responsible for ensuring that our datasets are high-quality, ethically sourced, and continuously enriched with useful metadata.  

You will not only lead the development and maintenance of internal tools and platforms for dataset management and training but also will design and operationalize an open-source strategy for helping Adobe contribute to the open-source community in the Generative AI training and data frameworks space. Our tools are built from the ground up and integrate seamlessly with widely used machine learning platforms such as pytorch, to optimize the efficiency in speed and cost of training on substantial datasets.  

You will also collaborate with our legal and ethics department, aligning with data privacy and access regulations and analyzing our datasets’ inherent biases and investing in reducing them. We take our customer’s privacy very seriously at Adobe, and the managed datasets have to be continuously updated to respect the opt-in/opt-out customers’ settings. 

What you’ll do 

• Lead a team of machine learning engineers, applied scientists and systems engineers in designing, building and maintaining a robust, scalable and efficient ML training and data framework. 

• Lead the curation and organization of a centralized, ethically sourced training dataset repository for all the training groups at Adobe. 

• Lead the development and maintenance of internal tools and frameworks for dataset management and large-scale training with technologies such as pytorch, Parquet.  

• Drive best practices in machine learning model lifecycle management, data governance, and reproducibility.  

• Collaborate with research, product, and engineering teams across Adobe to align Machine Learning capabilities with business needs. 

• Monitor, analyze and report on the performance of the platform, identifying areas for improvement and making data-driven decisions to optimize the platform’s performance and return on investment. 

What you need to succeed 

• ​Excellent leadership skills, with the ability to inspire and motivate team members to achieve their best work. 

• Deep expertise in large scale data processing and training frameworks (e.g., pytorch, JAX, Tensorflow, Parquet, Scala). 

• Proficiency in cloud-based AI/ML platforms, relevant tools, and frameworks (e.g., AWS, GCP, Azure ML, Docker, Kubernetes). 

• Strong experience in modern machine learning including supervised and unsupervised deep learning models for image, and text processing, with a focus on transformer based large-scale networks. 

• Strong experience in best practices for data ETL pipelines for machine learning. 

• Strong experience in optimizing distributed training frameworks for deep learning. 

• Strong experience in establishing MLOps best practices for model monitoring, retraining, and deployment processes. 

• Strong experience in product management with a track record of delivering successful products and features in the AI/ML space. 

• A bachelor’s, master’s, or PhD degree in computer science, Electrical Engineering, or a related field, or equivalent industry experience. 

• Strong analytical and problem-solving skills, with the ability to think strategically and make data-driven decisions 

#FireflyGenAI

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $193,900 — $373,600 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

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.

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.

Adobe is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.
 

Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email [email protected] or call (408) 536-3015.

Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees.