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Ready to make your application Please do read through the description at least once before clicking on Apply. Changing the world through digital experiences is what Adobe is all about. We empower everyone—from emerging artists to global brands—to design and deliver exceptional digital experiences. Our passion lies in helping people create beautiful images, videos, and apps, and transforming how companies interact with customers across screens. We are committed to hiring the best talent and creating an inclusive environment where everyone is respected and has equal opportunities. We believe innovation can come from anywhere in the organization, and the next big idea could be yours! About the Role Adobe Firefly's Generative AI Services team is seeking a Principal Machine Learning Engineer to serve as the technical lead for our GenAI Services. In this role, you will lead a team of engineers to build scalable, high-performance generative AI systems powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere. Your responsibilities include architecting inference pipelines, optimizing models for latency and throughput, and building APIs that integrate Adobe's and third-party generative models. As a hands-on leader, you will address complex engineering challenges, set technical direction, and mentor ML engineers. Job Responsibilities Lead the development of core GenAI services and APIs integrating generative models into Adobe's products. Design and architect ML workflows for enterprise-scale model customization, serving, and ecosystem integration. Build and optimize GPU-accelerated pipelines for model training and inference, focusing on performance, scalability, and reliability. Provide hands-on technical leadership , guiding engineers through architecture, design, and best practices. Research and evaluate emerging ML and MLOps technologies to improve engineering velocity and system performance. Drive cross-functional alignment by collaborating with Product Managers, TPMs, and engineering leaders to define and execute the roadmap. Lead design reviews and set technical standards to ensure system reliability and maintainability. Foster a culture of innovation and technical excellence within the team. Qualifications MS or PhD in Computer Science, Machine Learning, or related field, or equivalent industry experience. 8+ years in machine learning, including deploying models at scale. 3+ years leading large-scale, GPU-intensive GenAI systems. Deep experience with frameworks like PyTorch, CUDA, Triton, TensorRT, Nvidia Dynamo, and Python . Strong understanding of generative architectures such as diffusion models, transformers, and GANs . Proven success leading cross-functional teams through complex projects. Excellent communication and leadership skills. Preferred Qualifications Experience with model serving, orchestration, and GPU resource management . Hands-on expertise in Kubernetes, distributed systems, and MLOps platforms . #FireflyGenAI Our compensation varies based on geographic markets, with the U.S. pay range for this role being $193,900 to $362,400 annually. Salary depends on location, experience, and skills. The recruiter can provide specific details during hiring. For sales roles, salaries are expressed as total target compensation (base + commission). Non-sales roles are based on a fixed salary with potential short-term incentives. Some roles may also be eligible for long-term incentives like equity awards. State-Specific Notices: California : Adobe considers qualified applicants with arrest or conviction records in accordance with laws and ordinances. Colorado : The application window remains open until the specified date and time, in compliance with pay transparency laws. Massachusetts : It is unlawful to require lie detector tests for employment in Massachusetts. Violations may result in penalties. Adobe is an Equal Employment Opportunity employer. We do not discriminate based on protected characteristics. For accommodations, contact accommodations@adobe.com or call (408) 536-3015.

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