Sr. Machine Learning Engineer, Adobe Firefly Services

Senior Machine Learning Engineer

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!

Adobe Firefly's Generative AI Services team is seeking Senior Machine Learning Engineers for our GenAI Services area. In this high-impact role, you will work with a team of talented engineers in building scalable, high-performance generative AI systems-powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere. You will design and develop efficient inference pipelines, optimize models for latency and throughput at inference, and build APIs and ecosystems that integrate both Adobe's first-party and third-party generative models into Adobe suite of products that serve individual and enterprise customers. You will tackle Adobe's most complex engineering challenges at the forefront of the industry, set technical direction, and mentor other ML engineers.

Job Responsibilities

• Design and development of core GenAI services and APIs that integrate a wide range of generative models into Adobe's flagship products.
• Design and build ML workflows for enterprise-scale model customization, serving, and ecosystem integration.
• Collaborate with Adobe Research and other model developer teams with a focus on model inference strategies and productization of those model.
• Build and optimize GPU-accelerated pipelines for both (customized) model training and inference-prioritizing performance, scalability, and reliability.
• Foster a culture of innovation, technical excellence, and continuous improvement across the organization.

What You'll Need to Succeed

MS or PhD in Computer Science, Machine Learning, or a related field-or equivalent industry experience. 7+ years of experience in machine learning, including production-scale deployments. 3+ years of experience leading large-scale, GPU-intensive GenAI systems (training, inference, and optimization). Experience with GenAI frameworks and tools such as PyTorch, CUDA, Triton, TensorRT, Nvidia Dynamo, and Python. Good understanding of generative model architectures, including diffusion models, transformers, and GANs. Good communication and leadership skills, with a track record of driving alignment in matrixed organizations.

Preferred Qualifications Experience with model serving, inference, orchestration, and GPU resource management in large-scale environments. Hands-on expertise in Kubernetes, distributed systems, and MLOps platforms.

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 $162,000 -- $301,200 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.