Principal Machine Learning Services Engineer, Firefly Enterprise
Adobe Inc., San Jose, CA, United States
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
Firefly is the new family of creative generative AI models coming to Adobe products that offers a new way to conceptualize, build, and scale content. It's a natural extension of the technology Adobe has produced over the past 40 years.
We have a huge opportunity to provide scalable GenAI backed solutions to allow our Enterprise customers to power their experiences! We are hiring a Principal ML Services Engineer to help achieve our Enterprise goals!
What You'll Do
- Contribute to the backend services for Firefly that power the Generative AI features on Firefly website, Photoshop, Illustrator, Express, Stock and other applications/surfaces for Enterprise customers.
- Design and Develop GPU optimized, efficient model pipelines (training and inference) for custom Generative AI solutions like 'Train Your Own Model' using customer data.
- Define the architecture to support small and large premium customers for training and inference without compromising SLAs.
- Ensure a scalable, reliable cloud service with observability, logging and tracing to enable quick detection, understanding and resolution of run-time issues.
- Contribute to Project Colligo, the AI superhighway for inference and training that will manage and serve a collection of ML models in a highly scalable and resilient system.
- Develop critical aspects of the business logic in the Firefly services to ensure metering of usage, entitlement checks, quota limits and upsell workflows.
What You Need to Succeed
- Consistent track record building, optimizing and operating GPU intensive ML workloads in production environments.
- Several years' experience architecting cloud services and infrastructure for large scale use (5B+ requests per month).
- Deep understanding of model serving, orchestration, scaling, GPU resource management.
- Extensive, high level software engineering experience.
- Technology Skills: Python, ML, PyTorch, AIT, AOT, CUDA, GPU drivers, Kubernetes, AWS.
- Nice to have: Java.
#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 $189,400 -- $357,900 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.
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