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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Machine Learning Engineer - **Company:** Adobe Inc. - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $206,400.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Automated Storage and Retrieval Systems, Nvidia CUDA, Distributed Systems, Python (Programming Language), Machine Learning, Systems Integration, Retrieval-Augmented Generation, Large Language Models, Backend, Agentic-AI, Discretization, Adobe, AI Platforms, Kubernetes, Information Technology, Low Latency, Optimization Algorithms, Machine Learning Operations, TensorRT - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_f2496880ebd31cf2b98486027a3754c5 ## About the Role * 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 asPyTorch, 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 reasonaboutoutput 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, witha track recordof driving alignment in matrixed organizations. * Excellent communication and technical leadership skills., * Experience with model serving, orchestration, and GPU resource management in large-scale environments. * Hands-onexpertisein Kubernetes, distributed systems, andMLOpsplatforms. * Experience with RAG architectures and multi-turn, agentic conversational systems. * Experience with quantization, distillation, or other model-optimization techniques for inference., * 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 ## Description * 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 integratesfirst-partyand 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 andmanagementownership. 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 aligntechnical 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 toalign onshared 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 MLservingworkflows for enterprise-scale model customization, deployment, and ecosystem integration - including externalizable, self-serve fine-tuning flows. * Co-develop andoptimizeGPU-accelerated inference pipelines - prioritizing latency, throughput, scalability, and reliability - using tools such asPyTorch, CUDA, Triton, andTensorRT. * Design andarchitectthe 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 andMLOpstechnologies - 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.