ML Ops Engineer for Media Platform

Adobe
San JosePosted 1 March 2026

Job Description

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! 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! Our Team The Digital Video and Audio (DVA) organization at Adobe creates the world's best tools for telling stories. Our team is building Adobe's newest video tools: Premiere Mobile and Firefly Video Editor for Web. The Opportunity Come help build the new cloud storage, compute, and AI/ML platform that is powering Adobe’s next generation of professional video creation tools. This platform has machine learning and generative technologies at its core, and is enabling our customers to creatively and productively work with video in ways they never could before. You will join a team of engineers with extensive backgrounds in infrastructure and distributed systems, media processing, and machine learning. You will be responsible for creating, scaling, and operating infrastructure that handles media storage and compute on a global scale. Impact You'll Make You will be instrumental in ensuring that our infrastructure is reliable, scalable, efficient, and secure. You will have the opportunity to both delight our customers with fast, always-available delivery of Adobe's groundbreaking technologies, and save our company money by reducing compute and storage costs. Key Responsibilities Architect, build, and operate Kubernetes-based infrastructure for ML and media compute Manage usage of cloud (AWS, Azure, GCP) storage, database, and key-value-store systems, ensuring they deliver efficient performance Configure and monitor our platform's connections to third-party APIs for media processing Automate deployment, monitoring, and incident response for AI-powered applications Collaborate with engineering, product, and ML research teams to optimize workflows and infrastructure for rapid iteration Implement infrastructure-as-code and configuration management best practices Ensure compliance with security and privacy standards across environments Drive continuous improvement in reliability, performance, and developer productivity Troubleshoot and resolve infrastructure issues in production and development environments Qualifications 5+ years of experience in ML Ops, DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles Deep expertise with cloud platforms (Azure, AWS, GCP) and container orchestration (Kubernetes, Docker) Proven experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps, etc.) Experience with infrastructure-as-code development approaches (Terraform, etc.) Strong scripting and automation skills (Python, Bash, etc.) Experience supporting AI/ML workloads and data pipelines Familiarity with monitoring, logging, and alerting tools (Prometheus, Grafana, Splun ... (truncated, view full listing at source)
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