Computer Scientist

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 Role Overview We are looking for a Site Reliability Engineer with a strong developer mindset and 4-5 years of experience to help us build and operate scalable reliable systems This is not a just keep the lights on SRE role you ll be writing production-grade code building tools automating platforms and contributing directly to both infrastructure and developer productivity The ideal candidate brings together SRE discipline deep networking knowledge Kubernetes expertise and solid software engineering skills with an understanding of GPU-based workloads and AI ML inference training pipelines About the Platform You ll be working on a cutting-edge platform designed to train and serve large-scale machine learning models The platform supports everything from small-scale experimentation to massive distributed training jobs running on GPU clusters It provides developers and ML engineers with the tools to quickly onboard monitor and scale their workloads whether it s a lightweight prototype or a production-grade deep learning model powering real-world applications Key platform features include Dynamic GPU orchestration using Kubernetes Built-in support for training and inference workflows End-to-end observability and cost tracking High developer velocity via self-service tooling Your contributions will directly impact the reliability scalability and efficiency of this platform and enable AI teams to innovate faster What You ll Do Build tools APIs and platforms to improve reliability deployment and performance Architect and scale Kubernetes-based infrastructure for high-performance workloads including GPU Write clean efficient and maintainable code in Python Go or similar languages Own and evolve CI CD pipelines infrastructure-as-code systems Terraform Helm and service observability Troubleshoot and resolve complex system network and application-level issues Participate in blameless incident response root cause analysis and reliability reviews What You Bring Core Requirements 4-5 years of experience in SRE DevOps or platform engineering roles Strong development background with fluency in Python Go or similar languages Solid understanding of Kubernetes internals workload orchestration and Helm Deep knowledge of networking fundamentals DNS TCP IP routing VPNs firewalls Experience with infrastructure automation and configuration management Understanding of GPU scheduling resource allocation and NVIDIA ecosystem tools Familiarity with service mesh observability stacks Prometheus Grafana OpenTelemetry and cloud-native patterns Bonus Points Experience supporting AI ML pipelines especially GPU-based training inference Contributions to open-source projects or internal developer platforms Why This Role You ll write software not just YAML You ll get to work on real AI infrastructure challenges not just buzzwords You ll have impact across developer productivity platform scalability and service reliability You ll join a team that values code quality systems thinking and ownership Adobe is proud to be an employer We do not discriminate based on gender race or color ethnicity or national origin age disability religion sexual orientation gender identity or expression veteran status or any other applicable characteristics protected by law Adobe aims to make Adobe com accessible to any and all users If you have a disability or special need that requires accommodation to navigate our website or complete the application process email or call 408 536-3015