Principal Machine Learning Engineer

Role details

The Opportunity Firefly Foundry is Adobe's enterprise managed-service offering for custom multimedia generative AI — deep-tuned image, video, and 3D models built on each customer's IP, paired with creative production workflows and a media-intelligence layer, and deployed across new and existing Adobe surfaces and products, including Firefly, Photoshop, Illustrator, Express, Stock, and Premiere. We are hiring a Principal Machine Learning Engineer to serve as the technical lead for our GenAI Services area. This is not a model-training or research role — it is the senior-most hands-on engineering authority over how our generative models are architected, optimized , and served at enterprise scale. You will set the inference architecture and technical standards that a growing organization of engineers builds against, co-develop and optimize the inference code that makes those systems fast and cost-efficient, and architect the APIs and product backend that let Adobe's first-party and third-party models reach both internal applications and external plugin integrations. Where the Director owns the multi-year technical strategy, headcount, and company roadmap for the org, you own the architecture, technical depth, and hands-on execution that make that strategy real — spanning multiple engineering teams without owning their people management. What this role owns The technical architecture for composing, optimizing , and serving heterogeneous generative model pipelines — LLMs, diffusion and transformer-based image/video models, RAG and retrieval systems, multi-turn agentic flows, and 3D/mesh pipelines — across the GenAI Services area. The optimization strategy for inference performance: latency, throughput, and cost-to-serve across model families and GPU fleets. The system design standards for pipeline composition, multi-tenant serving, and the product backend/API and plugin surface that integrates first-party and third-party generative models into Adobe's flagship products. Technical direction across multiple engineering teams as the principal authority on architecture and design — a cross-team scope, distinct from the Director's org-wide roadmap and management ownership. Who you will partner with Applied Science — to translate research models and emerging techniques into production-grade inference architecture. Director, ML Engineering and ML Engineering leadership — to align technical architecture with organizational strategy and priorities. Product Managers and TPMs — to define and deliver against the roadmap for GenAI services and APIs. Firefly Foundry Studio and AI Platform — to translate creative production workflows into performant services and to align on shared infrastructure and serving primitives. What you will do Lead the development of core GenAI services and APIs that integrate a wide range of first-party and third-party generative models into Adobe's flagship products. Architect ML serving workflows for enterprise-scale model customization, deployment, and ecosystem integration — including externalizable, self-serve fine-tuning flows. Co-develop and optimize GPU-accelerated inference pipelines — prioritizing latency, throughput, scalability, and reliability — using tools such as PyTorch , CUDA, Triton, and TensorRT . Design and architect the product backend and plugin ecosystem that lets internal applications and external integrations consume Firefly Foundry's model services. Provide hands-on technical leadership: guide engineers through architecture, design, implementation, and best practices, and mentor a growing organization of ML engineers. Research and evaluate emerging inference and MLOps technologies — serving runtimes, quantization , GPU scheduling — to improve engineering velocity and system performance. Lead design reviews and set technical standards, ensuring high reliability and maintainability across systems. Drive cross-functional alignment with Product Managers, TPMs, and engineering leaders to define and deliver on the roadmap. Foster a culture of technical excellence and continuous improvement across the organization. What you bring MS or PhD in Computer Science, Machine Learning, or a related field — or equivalent industry experience. 8+ years of experience in machine learning engineering, including production-scale deployment and serving — not training or research experimentation. 3+ years leading the technical direction of large-scale, GPU-intensive GenAI inference systems — serving, architecture, and optimization. Deep experience with inference frameworks and tools such as PyTorch , CUDA, Triton, TensorRT , Nvidia Dynamo, and Python. Strong understanding of generative model architectures — diffusion models, transformers, GANs, LLMs — sufficient to make architecture and optimization calls and reason about output quality, in partnership with Applied Science. Proven experience architecting multi-model pipelines and serving them behind APIs at enterprise scale. Experience designing product backend systems and plugin architectures consumed by internal applications and external integrations. Proven success leading cross-functional teams through complex, high-stakes technical initiatives, with a track record of driving alignment in matrixed organizations. Excellent communication and technical leadership skills. Preferred Qualifications Experience with model serving, orchestration, and GPU resource management in large-scale environments. Hands-on expertise in Kubernetes, distributed systems, and MLOps platforms. Experience with RAG architectures and multi-turn, agentic conversational systems. Experience with quantization, distillation, or other model-optimization techniques for inference. Education Master's or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience building and leading production-scale ML systems. #FireflyGenAI About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleas